So many people are learning machine learning. What should you do to stand out?

There it was. Podcasts, YouTube, blog posts, machine learning here there changing this changing that changing it all.

I had to learn. I started. Andrew Ng’s Machine Learning course on Coursera. A bunch of blog posts. It was hard but I was hooked. I kept going. But I needed some structure. I put a few courses together in my own AI Masters Degree. I’m still working through it. It won’t finish. The learning never stops.


You know this. You’ve seen it happening. You’ve seen the blog posts, you’ve seen the Quora answers, you’ve seen the endless papers the papers which are hard to read the good ones which come explained well with code.

Everyone is learning machine learning.

Machine learning is learning everyone.

How do you stand out?

How how how.

A) Start with skills

The ones you know about, math, code, probability, statistics. All of these could take decades to learn well on their own. But decades is too long. Everyone is learning machine learning. You have to stand out from everyone.

There are courses for these things and courses are great. Courses are great to build a foundation.

Read the books, do the courses, structure what you’re learning.

This week I’m practising code for 30-minutes per day. 30-minutes. That’s what I have to do. When I don’t feel like practicing. I’ll remind myself. These are the skills I have to learn. It’ll be yes or no. It’s my responsibility. I’ll do it. Yes.

Why skills?

Because skills are non-negotiable. Every field requires skills. Machine learning is no different.

If you’re coming from zero, spend a few months getting into the practical work of one thing, math, code, statistics, something. My favourite is code, because it’s what the rest come back to.

If you’re already in the field, a few months, a fear years in, reaccess your skills, what needs improving? What are you good at? How could you become the best in the world at it? If you can’t become the best in the world, combine with something else you’re good at and become the best in the world at the crossover.

B) Got skills? Good. Show them.

Ignore this if you want.

Ignore it and only pay attention to the above. Only pay attention to getting really good at what you’re doing. If you’re the best in the world at what you do, it’s inevitable the world will find out.

What if you aren’t the best in the world yet?

Share your work.

You make a website.

I made this up. It might exist.

On your website you share what you’ve been up to. You write an article on an intuitive interpretation of gradient descent. There’s code there and there’s math there. You’ve been working on your skills so to give back you share what you’ve learned in a way others can understand.

The code tab links to your GitHub. On your GitHub you’ve got examples of different algorithms and comments around them and a tutorial on exploratory data analysis of a public health dataset since your interest in health. You’ve ingested a few recent papers and tried to apply it to something.

LinkedIn is your resume, you’ve listed your education, your contributions to different projects the porjects you’ve built the ones you’ve worked on. Every so often you share an update of your latest progress. This week I worked on adding in some new functions to my health project.

You’re getting a bit of traction but it’s time to step it up. You’re after the machine learning role at Airbnb. Their website is so well designed you stayed at their listings you’re a fan of what the work they do you know you could bring them value with your machine learning skills.

You make another website.

I made this one up too. Kudos if you’re already on it.

You send it to a few people on the Airbnb recruitment team you found on LinkedIn with a message.

Hi, my name is Charlie, I hope this finds you well.

I’ve seen the Machine Learning Engineer role on your careers page and I’d like to apply.

I made this website which shows my solutions to some of your current challenges.

If you check it out, I’d love your advice on what best to do next.

5/6 of the people you message click on it. This is where they see what you’ve done. You built a recommendation engine. It runs live in the browser. It uses your machine learning skills. Airbnb need a machine learning engineer who has experience with recommendation engines. They recommend a few things.

3 reply with next steps of what to do. The other 2 refer to other people.

How many other people sent through a website showcasing their skills?


Maybe you don’t want a job. Maybe you want to research. Maybe you want to get into a university. The same principles apply.

Get good at what you do. Really good.

Share your work.

How much?

80% skills.

20% sharing.


How to be a leader: Rap & Rock Climbing edition

You see there’s leaders.

And there’s followers.

But I’d rather be a dick than a swallower.

Those are the lyrics to Kanye West’s song New Slaves.


In other words, Kanye would rather be seen as a dick to some people and speak his truth, than have to bite his tongue and not say what’s on his mind.

Does this suit everybody?

No. It’s implied in the lyrics anyway.

Being a leader isn’t about pleasing everybody.

Being a leader takes courage. The courage to do things not everyone will agree with.

Not everyone agrees with Kanye West.

He’s loud.

He speaks his mind.

He has no filter.

But you can’t argue with his ability to perform. To do things others can’t.

Can you lead without being loud?

How about from the inside of a van?

I’m talking living 24/7 in a van, eating nothing but beans and vegetables. With chalk everywhere. On the carpet, on the bed, on the chairs.


Rock climbers use chalk to absorb the sweat on their hands and increase the friction on their holds. When you’re holding onto a ledge a couple of millimetres wide, sweaty hands are no good.

If you’ve ever used chalk, you know how easily it spreads everywhere.

Alex Honnold is a rock climber. His style is free solo. Free solo means without a rope or any assistance. None. Roll up to the base of the mountain and start climbing.


I needed chalk whilst I was watching Free Solo, the documentary detailing his journey to free soloing El Capitan.

The first time he tried, he pulled out 400ft in. There was a whole camera crew from National Geographic there and everything. Yet he made the call.

“I’m not feeling it.”

The majority of his free solos he’s done without telling anyone. He prefers it that way.

“What’s more important to me is making to the top, I don’t care if it’s filmed or not.”

I’m not going to ruin the rest of the documentary for you because I think you should watch it.

Alex is a leader.

But Kanye and Alex couldn’t be more different.

One climbs mountains without a rope and lives in a van. The other owns a fashion brand, a record label and writes songs.

Do you need to climb a mountain without a rope to be a leader?


Do you need to be multi-millionaire multi-award winning artist to excel in leadership?


The thing they both have in common is they do things others can’t.

They take on challenges others would say, I can’t believe he’s doing that.

Does it always work?


Leaders know this.

Then they show up and say, let’s find a way anyway.


6 Tips to Keep Yourself From Getting Distracted Whilst Studying

Tomorrow happens.

I get up. I’m tired. I went to bed late. Distracted by my phone. Sophie was texting me.

Did she reply?

She didn’t. But there’s other red bubbles. More red bubbles. I tap one. Then another. I’ve been up for 46-minutes. I have no idea what I’ve done.

I decide that’s enough phone time for today. It goes in the drawer.


A) $1000/hour

If there was $1000 on the table, would you take it?

Yes of course, I would.

How about if someone else was at the table?

They turn to you.

Give me $1000.

Would you give to them?

I wouldn’t.

And if you wouldn’t either, why do you give away your time so easily?

Value your time at $1000 per hour.

“Would I pay $1000 per hour to do this?”

Study and education. Yes.

Random online internet surfing. No.

Seeing those people you knew 6-years ago buy a boat and go fishing with their new friends. No.

The list of things gets shorter real quick.


B) Keep the energy bar high

Tomorrow happens again.

My energy bar is already low.

Poor sleep and poor foods over the past couple of days have clogged everything.

My energy. Clogged.

My gut. Clogged.

My brain. Clogged.

How am I supposed to study whilst everything is clogged?

I decide I need to sleep more and eat better and begin at once.


C) What the hell am I doing?

A third tomorrow happens.

That’s three yesterdays with nothing. Three nothings.

But my energy bar is full today. My phone is away. I’m ready.

I sit down.

The void consumes me. There’s a pile of this and that and a stack of thoughts. I’m drowning in thoughts. Too much. What the hell am I doing?

I spend 17-minutes trying to decide. I figure it out. I put a few things down. Lost in thought but found in the words.

Math work.

Coding practice.


Yeah, that’s good. Three things, that’s enough.


D) Time it

Math work got done but none of the others.

I’m starting to get this starting to get the hang of things.

Math work was good. My energy bar was high. Top sleep and food does the trick.

It got me. Got me good. The math. I got lost. Lost in the patterns. I was on a roll. Connecting the dots. Playing.

I lost track of time. These things happen when you’re playing.

Next time I must put a time limit on each one. Not too much. But not too little I can’t do what I need to do.


E) Playing

I set up a timer. I want these things done. I’m getting better.

A full energy bar.

Valued time. $1000 per hour!

A list of things to do.

Look at me go!

The timer is running. 25-minutes of playing.

I learned it from the math study.

Work is playing. Studying is playing. I’ve convinced myself. They’re the same. It helps you know. It does.

I think if I can learn this and then that, I’m in a game, I can turn it into a game. Study becomes play.


F) Enough

All this time playing I finish exhausted. All of the list done. A depleted energy bar. Thousands of dollars of time and effort dedicated.

I lay in bed. Still intrigued. The best way to be. But I know I must rest. The sleep will help. Help me focus. Keep my energy bar up.

I can it enough. When I’ve reached it, I call it. I’ve done a good job today. There’s more to do though. There’s always more to do.

My list of what to do.

My timer to help with the list. $1000 per hour.

My full energy bar. The sleep and food. And the bending exercises.

My phone away.

These things will help.

I lay in bed. Still intrigued.

Tomorrow happens.


How does machine learning get used by regular people?

You wake up. You check your phone. Its been on charge all night. The battery usage from the previous day was recorded and will be used along with previous use history to maximise charge. Machine learning.

Your new emails load, there’s an email from Steve. He wants the thing done earlier. It’s always earlier. Faster.

There are a few more emails. One from Amazon. Your package is going to be shipped today. And a new Uber promotion. 10% of rides for this week. You click the link and apply the code.

The rest of the emails are garbage. Stuff you’ve subscribed to but didn’t need. At least you subscribed to them.

There’s another 15 emails you don’t see. They’re in the spam folder. Your email client scanned through the text as they came in and put them there. Machine learning.

It isn’t perfect though. You could’ve been a millionaire. A billionaire! If only you’d seen the email and sent that Nigerian Prince your bank details.

A charge comes through on your card. The amount pops up on your screen. $37.85 from Amazon. Another email. Your order of Machine Learning is Everywhere is on its way.

Another charge. Gym membership for the week.

All this money, flying across the internet. You’d think someone could tap into this stream and take some. They try but they can’t. Even when they get your card. They try to buy something. It might go through the first time but by the second time, the card is dead.

What happened?

Your bank detected the fraud and froze your account. The transaction in another country wasn’t like the other ones you’ve made in the past.

Another email.

We’ve detected fraud and frozen your account. Don’t worry, your funds are safe. To sort this out, you can contact us here.

There’s no way any person could monitor all the transactions happening. Machine learning.

You call the bank. Your card has been unfrozen and the funds will be back in your account in 24-hours.

It’s 8:34 am. The Uber app pops up at the bottom of your phone. Your calendar says work starts at 9 and based on previous trips, your phone knows it takes about 16-minutes to get there. Machine learning.

6 drivers are close by. Less than usual. Your work address is already preloaded. You get matched with the Black Prius, licence plate, 889LYJK. Machine learning.

The driver takes a route you’ve never been. And then the map corrects itself to adjust for traffic. Machine learning.

Josh is in Bali. Sarah had a birthday party on the weekend. Their photos are on Instagram. An ad appears for those new shoes you’ve been looking at. The ones with the orange. The ad was delivered in your feed amongst photos from the people you’ve been following — there’s a balance. Too many ads and you’d stop using Instagram. Machine learning.

And the naked picture from HotPix2928133Q in your discover tab? You didn’t see it because it was filtered out. Machine learning.

The traffic is bad. Car, car, car, car, truck, car, bus, car. Nose to tail. The Black Prius crawls ahead. The cameras in the front grill stop it from getting too close to the car in front. Machine learning.

You’re not even at work yet.

Tomorrow is your day off. What’s the weather like? Open the weather app. Sunny with a chance of rain, 18% chance. Where’d the chance come from? Machine learning.

Breakfast: a bagel with bacon and avocado. You’ve been trying to cut the carbs but Bagel Boys do it so well. So well. The bagels are a dream. They’re $7 but you’d pay $10.

You can't see them but they're there. The drones monitoring the wheat crops. They look for crop stress. Too much stress is never good. Too much stress leads to death. The drones help the farmer. They help the farmer so you can taste the Bagel Boys glory. Machine learning.

The address reader knows what characters look like. It reads your address on the package and sends it down the chute. Machine learning.

All the information is encoded in the barcode but not everywhere has the same barcode system. The driver picks up a collection of parcels. Your book is one of them. Your house is close to the depot so it's delivered before 10.

It's a good book. A best seller. You want to tell Ankit it arrived and tell him he should read it too. Your phones screen brightness changes as you take a photo. The photo looks so crisp. You’re a real photographer now. The book is in focus and the background is blurred. All with the tap of a button. Magic? No. Machine learning.

Machine Learning is Everywhere.

Future book cover? haha

Future book cover? haha


How I study five days a week

I had no job.

Then I started driving Uber on the weekends to pay for my studies.

I loved meeting new people but I hated driving a car all the time. Traffic, stop, start, fuel, the air, the aircon, all of it.

I studied machine learning. All day, five days a week. And it was hard. It's still hard.

9-months in, I got a job.

It's the best job I've ever had.

A) Fix your environment

Your grandfather’s first orange farm failed.

The soil was good. The seeds were there. All the equipment too. What happened?

It was too cold. Oranges need warm temperatures to grow.

Your grandfather had the skills to grow oranges but there was no chance they were growing in a cold climate.

When he moved to a warmer city, he started another orange farm.

12-months later, your grandfather was serving the best orange juice in town.

Studying is like growing oranges.

You could have a laptop, an internet connection, the best books and still not be motivated to study.


Because your environment is off.

Your room is filled with distractions.

You try to study with friends but they aren’t as dedicated as you.

Whatsapp goes off every 7-minutes.

What can you do?

Clean your room. Find a different study group. Friends are great when it comes to friend time but study time is study time. Put your phone in a drawer for an hour.

Fix your environment and let the knowledge juices flow.

B) Set the system up so you always win

Problem 13 has you stumped. You’re stuck.

You wanted to get it done yesterday but couldn’t.

Now it’s time to study but you know how hard you worked yesterday and got nowhere.

You’re putting it off.

You know you should be doing it.

But you’re putting it off.

It’s a cycle.


The pile of books stares at you. Problem 13.

You set a timer. 25-minutes.

You know you might not solve the problem but you can sit down for 25-minutes and try.

4-minutes in, it’s hell. Burning hell. But you keep going.

24-minutes in and you don’t want to stop.

The timer goes off and you set another. And then another. After 3 sessions, you solve the problem.

You can't always control whether you make progress with study. But you can control how much time you spend on something.

Can control: four 25-minute sessions per day.

Can't control: finishing every task you start every day.

Set the system up so you always win.

C) Sometimes do nothing

I did the Coursera Learning How to Learn course the other day.

One of the main topics was focused versus diffused thinking.

Focused thinking happens when you're doing a single task.

Diffused thinking happens when you're not thinking about anything in particular.

The best learning happens at the crossover of these two.

It's why you have some of your best thoughts in the shower. Because there's nothing else happening.

When you let diffused thinking takeover, it gives your brain space to tie together all of the things it absorbed during focused thinking.

The catch is, for it to work properly, you need time in both.

If you've set the system up so you do four 25-minute sessions of focused work, go for a walk after. Have a nap. Sit and think about what you've learned.

The world could do with more of nothing.

D) Embrace the suck

Studying sucks.

You learn one thing and forget it the next day.

Then another and forget it.



You spend the whole weekend studying, go to work on Monday and no one knows.

Then after a year of studying something you realise how much more there is to still learn.

When will it end?

It doesn't. It's always day one.

Embrace the suck.

E) The 3-year-old principle

I was at the park the other day.

There was a young boy running around having the time of his life.

Up the slide, down the slide, in the tree, out of the tree, in the dirt, out of the dirt, up the hill, down the hill.

He was laughing and jumping then laughing again.

His mum came over to pick him up.

"Come on, Charlie, we've got to go."

He kept laughing as she carried him away, waving his blue plastic shovel.

What is it that fascinated him?

He was playing. He was having fun. The whole world was new.

Our culture has a strict divide between work and play.

Study is seen as work.

You're supposed to study to get more work. You're supposed to work to earn money. The money buys you leisure time. Then and only then can you be like Charlie and run around laughing.

If you have it in your head study is work, it will be hell.

But suppose, you have the idea about it that studying is the process of going through one topic and then to the next.

Connecting different things like a game.

The same feeling about it as you might have as if you were Charlie going down the slide.

You learn one thing, you use it to learn something else, you get stuck, you get over it, you learn another thing. And you make a dance out of it.

Do this and you'll finish a study session with more energy than you started.

This is the 3-year-old principle. Seeing everything as play.

That's enough for now.

It's bedtime.

That's a bonus.

F) Sleep

Poor sleep means poor studying.

Don't trade sleep for more study time. Do the opposite.


The most precious thing you can give someone

She was screaming.

You don’t know what’s happening Gregory!

You just wait Greg, I know what you’re up to!

More screaming.

There isn’t anything I don’t know Gregory!

I walked across the street. What was happening? Why didn’t Greg know? What did she know about Greg? There wasn’t anything she didn’t know. Was she an oracle?

I should’ve talked to her. I could’ve asked her about life. She could’ve help me figure it all out.

I pretended like I did.

Can I ask you something?

There isn’t anything I don’t know Daniel!

What’s the most precious thing you can give to someone else?

Give them a feeling!


Something that penetrates their soul! Get deep! Really deep! Make it bubble up!

Make what bubble up?

You want it to be there in a year! In 5-years! When they’re in a cafe reading a newspaper and they look up and get nauseous thinking of the feeling! You want it to be so good it comes back! It always comes back!

I get it but why are you screaming?

Why do you think! Do you not listen! You’re just like Gregory! You don’t know what’s happening!

Imagining is almost as good as the real thing. Sometimes it’s better. Sometimes worse. Far worse.

She made me feel something. Unintentional or intentional? Who knows. She was talking to Gregory. Gregory didn’t know what was happening.

Her purple top left her stomach uncovered. And the pants she had on were dirty. Maybe she was crazy. Maybe I was crazy for taking lessons imaginary lessons from a screaming lady on the street. Gregory wasn’t. Gregory didn’t know what was happening.

Financial freedom has two extremes. One where you can buy whatever you want. The other where you don’t care about anything. She was financially free. Rich. Rich with the most valuable currency there is. Rich with effect. Effect on others. Effect on me. She had an audience. Everyone crossing the street was in awe. What was Greg up to?

Effect is precious. It can last an instant but be remembered for a lifetime. It can happen once and then again 1000 more times.

You could be sitting in a cafe in 5-years reading the newspaper. Look up for a second. Your stomach does a backflip. And it comes back, the feeling all over again.

How she smiled at you.

Or how she screamed from across the street.

Once you give a feeling to someone, it’s there. Always there.


Self-Studying Machine Learning? Remind yourself of these 6 things

We were hosting a Meetup on robotics in Australia and it was question time.

Someone asked a question.

“How do I get into artificial intelligence and machine learning from a different background?”

Nick turned and called my name.

“Where’s Dan Bourke?”

I was backstage and talking to Alex. I walked over.

“Here he is,” Nick continued, “Dan comes from a health science background, he studied nutrition, then drove Uber, learned machine learning online and has now been with Max Kelsen as a machine learning engineer for going on a year.”

Nick is the CEO and Co-founder of Max Kelsen.

I stood and kept listening.

“He has documented his journey online and if you have any questions, I’m sure he’d be happy to help.”

The questions finished and I went back to the food.

Ankit came over. He told me about the project he was working on to use machine learning to try and understand student learning better. He was combining lecture attendance rates, time spent on the online learning portal, quiz results, plus a few other things. He’d even built a front-end web portal to interact with the results.

Ankit’s work inspired me. It made me want to do better.

Then a few more people started coming over and asking questions about how to get into machine learning. All from different fields.

This is the hard part. I still see myself as a beginner. I am a beginner.

Am I the right mentor?

The best mentor is someone who’s 1-2 years in front of you. Someone who has just been through what you’re about to go through. Any longer and the advice gets fuzzy. You want it when it’s fresh.

My brother is getting into machine learning. Here’s what I’ve been saying to him.

A) Get some Python foundations (3-4 months)

The language doesn’t really matter. It could be R, Java, Python, whatever. What matters is picking one and sticking with it.

If you’re starting out, you’ll find it hard to go wrong with Python.

And if you want to get into applied machine learning, code is compulsory.

Pick a foundations course from online and follow it through for a couple of months. Bonus points if it’s geared towards teaching data science at the same time. DataCamp is great for this.

It’ll get hard at times but that’s the point. Learning a programming language is like learning another language and another way of thinking at the same time.

But you’ve done it before. Remember when you were 3? Probably not. But people all around you were using words and sounds you’d never heard before. Then after a while, you started using them too.

B) Start making things when you’re not ready

Apply what you’ve learned as soon as you can.

No matter how many courses you’ve completed, you’ll never be 100% ready.

Don’t get lured into completing more courses as a sign of competence.

This is one thing I’d change if I went back and started again.

Find a project of your own to work on and learn through being wrong.

Back to your 3-year-old self. Every 3rd word you said would’ve been wrong. No sentence structure, no grammar either. Everything just came out.

C) There’s a lot out there so reduce the clutter

There are plenty of courses out there. All of them great.

It’s hard to find a bad one.

But here’s the thing. Since there are so many, it can be hard to choose. Another trap which can hold you back.

To get around this, I made my own AI Masters Degree. My own custom track to follow.

You can copy it if you want. But I encourage you to spend a few days doing research of your own and seeing what’s best for you.

As a heads up, three resources I’ve found most aligned to what I do day-to-day are, the Hands-On Machine Learning Book, the fastai Machine Learning course and the Applied Data Science with Python course on Coursera.

Bookmark these for after you’ve had a few months Python experience.

D) Research is pointless if you can’t apply it

You’ll see articles and papers coming out every day about new machine learning methods.

Ignore them.

There’s no way to keep up with them all and it’ll only hold you back from getting your foundations set.

Most of the best machine learning techniques have been around for decades. What’s changed has been an increase in computing power and the availability of data.

Don’t be distracted by the new.

If you’re starting out, stick to getting your foundations first. Then expand your knowledge as your project requires.

E) A little every day

3-year-old you was a learning machine (a machine learner?).

In a couple of years, you went from no words to talking with people who had been speaking for decades.


Because you practised a little per day.

Then the compound interest kicked in.

1% better every day = 3700% better at the end of the year.

If you miss a day, no matter, life happens. Resume when you can.

Soon enough you’ll start to speak the language of data.

F) Don’t beat yourself up for not knowing something

“Have you ever built a recommendation engine?”


“We’ve got a project that requires one as a proof of concept, think you can figure it out?”


Most people think learning stops after high-school or college. It doesn’t.

The scenario above happened the other week. I’d never built a recommendation engine. Then I did.

Failure isn’t bad if you’re failing at something you’ve done before. You’ve been walking your whole life but you don’t beat yourself up when you trip on your own feet. It happens. You keep walking.

But failing at something new is tough. You’ve never done it before.

Learning machine learning kind of goes like this.

1st year: You suck.

2nd year: You're better than the year before but you think you suck even more because you realise how much you don’t know.

3rd year: ???? (I’m not there yet)

Embrace the suck.

How much will beating yourself up for not knowing something help you for learning more?


Learning something new takes time. Every day is day one.

Learning isn’t linear.

Learning isn’t linear.

How would your 3-year-old self react to not knowing a word?

You’d laugh. Throw your hands in the air and then crawl around for a bit.

It’s the same now. Except you can walk.


Non-monetary sources of happiness

Walking outside and feeling the sun on my skin.

Staring at a body of water.

Taking walks for no reason.

Looking at the moon and having it remind me of a beautiful girl.

Coming home to two dogs who can barely control their shaking tails — correction: can’t control at all.

Sending a voice memo to a close friend.

Calling a close friend.

Spending time with a good friend.

Working on a hard problem.

Completing a tough workout.

Catching a deep breath, holding it, then letting it go.

Getting into bed and feeling my body realise it’s time to rest.

Hearing the next door neighbours play their loud stereo every night watching movies.

Seeing my mum walk in the house, smiling because she knows she’s done something to make us happy. She always knows how to make my brothers and I happy.

Thinking of my mum and writing about it.

Sitting here in my room on a Saturday night with nothing but the words.

Imagining what kind of story I can write next.

Knowing happiness is like the tide. It’s higher sometimes than others but it comes back.

Saying I love you to myself.

Saying I love you to others.

I read a story earlier from a son who said his second mother was coaching aerobics and then went to the doctor. She had cancer throughout her major organs and died two years later. He finished with a note saying ‘hug your people.’ Sad story but thinking of the note made me think of hugging others.


Sitting in a well-made chair.

Writing a letter to someone.

Using a pen. This keyboard is good. But pen and paper is better.

Listening to someone tell a good narrative. A girl told me a story about how she went to Greece to find her great Aunt. She had nothing but a name and the location of a small town on a small island. When she got to Greece the airline lost her luggage. She walked 3-hours with a backpack and found the town. She asked people the name and found a lady who acted as if she knew it. The lady didn’t speak a word of English. The lady took her to another lady. No English. The other lady got on Skype, her daughter was on the other side. She spoke English. They deciphered the message in a conversation triangle. She found her great Aunt. The great Aunt had a grandson, a 17-year-old boy. The boy spoke fluent English and was the leader of a gang on the island. There was nothing to do on the island except be in a gang, farm and ride motorbikes. For the next four days, she was given a chauffeured tour around the island on the back of a motorbike.

Realising how much I don’t know.

Learning new things. Today I read about the hotel bathroom principle. The idea was to dress well enough you could walk into a hotel and use their bathroom without them questioning it. Dressing well means you’ll be looking good. Looking good gives you a great shot of feeling good. Looking good and feeling good opens the door for serendipity. Hat tip: David Perell.

There are more but that’s enough for now.*

*Finsihing a piece of writing I’m proud of.

Breaking the rules.

Saying good night.

Good night.


The Five C's of Online Learning

This post originally appeared on Quora as my answer to 'Udacity or Coursera for AI machine learning and data science courses?'


Tea or coffee?

Burger or sandwich?

Rain or sunshine?

Pushups or pull-ups?

Can you see the pattern?

Similar but different. It’s the same with Udacity and Coursera.

I used both of them for my self-created AI Masters Degree. And they both offer incredibly high-quality content.

The short answer: both.

Keep scrolling for a longer version.

Let’s go through the five C’s of online learning.

If you’ve seen my work, you know I’m a big fan of digging your own path and online platforms like Udacity and Coursera are the perfect shovel. But doing this right requires thought around five pillars.


When you imagine the best version of yourself 3–5 years in the future, what are they doing?

Does it align with what’s being offered by Udacity or Coursera?

Is the future you a machine learning engineer at a technology company?

Or have you decided to take the leap on your latest idea and go full startup mode?

It doesn’t matter what the goal is. All of them are valid. Mine is different to yours and yours will be different to the other students in your cohort.

The important part is an insatiable curiosity. In Japanese, this curiosity is referred to as ikigai or your reason for getting up in the morning.

Day to day, you won’t be bounding out of bed running to the laptop to get into the latest class or complete the assignment you’re stuck on.

There will be days where everything else except studying seems like a better option.

Don’t beat yourself up over it. It happens. Take a break. Rest.

Even with all the drive in the world, you still need gas.


Sam was telling me about a book he read over the holidays.

‘There were some things I agreed with but some things I didn’t.’

My insatiable curiosity kicked in.

‘What did you disagree with?’

I was more interested in that. He said it was a good book. What were the things he didn’t like?

Why didn’t he like those things?

The contrast is where you learn the most.

When someone agrees with you, you don’t have to back up your argument. You don’t have to explain why.

But have you ever heard two smart people argue?

I want to hear more of those conversations.

When two smart people argue, you’ve got an opportunity to learn the most.

If they're both smart, why do they disagree?

What are their reasons for disagreeing?

Take this philosophy and apply it to learning online through Udacity or Coursera.

If they’re like tea and coffee, where's the difference?

When I did the Deep Learning Nanodegree on Udacity, I felt like I had a wide (but shallow) introduction to deep learning.

Then when I did Andrew Ng’s after, I could feel the knowledge compounding.

Andrew Ng’s teachings didn’t disagree with Udacity’s, they offered a different point of view.

The value is in the contrast.


Both partner with world-leading organisations.

Both have world class quality teachers.

Both have state of the art learning platforms.

When it comes to content, you won’t be disappointed by either.

I’ve done multiple courses on both platforms and I rate them among the best courses I’ve ever done. And I went to university for 5-years.

Udacity Nanodegrees tend to go for longer than Coursera.

For example, the Artificial Intelligence Nanodegree is two terms both about 3–4 months long.

Whereas Coursera Specializations (although at times a similar length), you can dip in and out of.

For example, complete part 1 of a Specialization, take a break and return to the next part when you’re ready. I’m doing this for the Applied Data Science with Python Specialization.

If content is at the top of your decision-making criteria, make a plan of what it is you hope to learn. Then experiment with each of the platforms to see which better suits your learning style.


Udacity has a pay upfront pricing model.

Coursera has a month-to-month pricing model.

There have been times I completed an entire Specialization on Coursera within the first month of signing up, hence only paying for one month.

Whereas, all the Udacity Nanodegree’s I’ve done, I’ve paid the total up front and finished on (or after) the deadline.

This could be Parkinson’s Law at play: things take up as much time as you allow them.

Both platforms offer scholarships as well as financial support services, however, I haven’t had any experience with these.

I drove Uber on weekends for a year to pay for my studies.

I’m a big believer in paying for things.

Especially education.

When I pay for something, I take it more seriously.

Paying for something is a way of saying to yourself, I’m investing my money (and time spent earning it), I better invest my time into too.

All the courses I’ve completed on both platforms have been worth more than the money I spent on them.


You’ve decided on a learning platform.

You’ve decided on a course.

You work through it.

You enjoy it.

Now what do you do?

Do you start the next course?

Do you start applying for jobs?

Does the platform offer any help with getting into the industry?

Udacity has a service which partners students who have completed a Nanodegree with a careers counsellor to help you get a role.

I’ve never got a chance to use this because I was hired through LinkedIn.

What can you do?

Don’t be focused on completing all the courses.

Completing courses is the same as completing tasks. Rewarding. But more tasks don’t necessarily move the needle.

Focus on learning skills.

Once you’ve learned some skills. Practice communicating those skills.


Share your work.

Have a nice GitHub repository with things you’ve built. Stack out your LinkedIn profile. Build a website where people can find you. Talk to people in your industry and ask for their advice.


Because a few digital certificates isn’t a reason to hire someone.

Done all that?

Good. Now remember, the learning never stops. There is no finish line.

This isn’t scary. It’s exciting.

You stop learning when your heart stops beating.

Let’s wrap it up

Both platforms offer some of the highest quality education available.

And I plan on continuing to use them both to learn machine learning, data science and many other things.

But if you can online choose one, remember the five C’s.

  1. Curiosity — Stay curious. Remember it when learning gets tough.

  2. Contrast — Remix different learning resources. All the value in life is at the combination of great things.

  3. Content — What content matches your curiosity? Follow that.

  4. Cost — Cost restrictions are real. But when used right, your education is worth it.

  5. Continuation — Learn skills, apply them, share them, repeat.


I’ve written and made videos about these topics in the past. You might find some of the resources below valuable.


What you should do with your spare time (to greatly improve your life)

You know the basics. The basics are easy.

  • Stay healthy

  • Stay hungry (for knowledge)

  • Avoid excess social media

  • Rest

  • Meditate

  • Take a yoga class

All the things you always see in a top 10 list. Take care of these all you’ll be in a good place.

But what else?

These are the things you’re scared to talk about with others. The thoughts that go through your head when you’re in bed.

Where does all this fear come from?

Tribe mentality.


7547 years ago, Johnny was part of a tribe. They hunted their own food and gathered what they needed.

Everyone had a role. Og collected the wood. Pog went out for berries.

One day Johnny decided to try something different. Instead of starting the fire, he went tree climbing to look for eggs.

When Johnny got back to the camp, the others weren’t happy.

No fire. No food. It was Johnny’s role to get the fire started. And we can all relate to how we feel after a night without dinner.

As Johnny walked back into camp, Tog put a spear through his chest. The tribe didn’t have room for outliers.

Fast forward to now and tribe mentality is still a thing. It’s ingrained in your biology.

Modern tribes don’t often come in the form of groups of spearing wielding individuals anymore. They come in the form of narratives.

You story you tell yourself is the tribe you belong to.

The deepest soul-suck of life begins when the story you tell yourself in your head doesn’t match the person you are in real life.

The good news?

You can work towards fixing this mismatch in your spare time.


Write down your thoughts. What’s holding you back? Most of the time you’ll find out your biggest hurdle is the story you’re holding on to.

Figure this out and your path will become clearer. It won’t be free of obstacles but you’ll be able to see them better.

But don’t confuse this for abandoning your duties to follow the magic trail.

The smart option for Johnny would’ve been to take care of the fire and then climb trees looking for eggs.

Johnny didn’t have a choice to change tribes. Leaving the tribe meant death.

Not anymore.

If your narrative isn’t fitting the one around you, use your spare time to rewrite it.

Photo by  Enoch Appiah Jr.  on  Unsplash

Photo by Enoch Appiah Jr. on Unsplash


How to Win Survivor — The Ultimate Strategy (and tips for being more confident and charismatic)

 ‘You’re just a bunch of fun aren’t you,’ she said.

‘Yeah, you’re right.’

‘I’m going to put you through to the next round,’ she was smiling, ‘you should hear back in a couple of days.’

I was applying for Survivor.

We had a Skype interview. The video quality was bad but she was beautiful.

Skype calls are like blind dates. I only talked to her via email beforehand. So I had no idea what she looked like.

Then we were dialing in. I had a pile of notes next to me. My brother and I had spent an hour or so practicing potential questions.

This was a big moment. We watched Survivor as kids, now I had the chance to be on it. A real life TV show. This was my chance!

The call connected.

‘Hello, can you hear me?’

‘Hi there, I can hear you.’

‘Oh wait, I can’t hear you, let me fix something.’

She fixed it.

‘There we go are you there?’

‘I’m here, nice to meet you,’ I smiled.

‘Okay, Daniel right?’

I forget her name.


‘Let’s do this.’

We got into it. And then the inevitable question was there.

‘Why should we choose you to be on Survivor?’

This one always comes up.

‘Why should we pick you for this job?’

Or even if it doesn’t, it comes up in other forms. When you’re a date, the other person is trying to figure out if you’re worth another date. But instead of asking ‘why should I keep seeing you?’, they ask questions like ‘are you religious?’

I told her why I should be on the show.

The same thing I told my brother when we practiced.

‘I should be on Survivor because no one else will play the game like me.’

Crap. Everyone would’ve said that.

‘How will you play the game differently?’

She was good.

‘Driving Uber I meet a new customer every 10-minutes. Working at Apple, I talked to a new person every 15-minutes.’

I went on.

‘To provide a quality service to someone, you have to figure out their needs. You have to understand them. That’s what I’m good at.’

‘I see.’

‘So no matter who’s there, I know I can get close to them, lead from the front and at the same time know when it’s time to sit back,’ I was rolling with it, ‘I call it the co-pilot strategy.’

She loved that.

‘The co-pilot strategy?’

I have no idea where this came from. An unexplainable force.

‘The co-pilot has enough control but isn’t the main guy. When it comes time to vote someone out, it’s often the one who stands out too much, the pilot.’

‘Oh I see, you’ll stay high enough in the tribe, but not too high to stand out.’

We kept talking. The conversation was supposed to go for 20-minutes. But we ended up going for an hour or so.

By the end of it I was in love. Or was it lust? I get the two mixed up.

She put me through to the next round. An in person group interview.

We had to attempt the same challenges as we would if we got on the show. My team won all the challenges.

After the group interview I saw a girl looking at Physics books at the bookstore. I stopped her on the way out.

‘Were you looking at Physics books?’

‘Yeah, I was.’

So how do you be so charismatic and confident you get through to the second stage of Survivor?


A) Practice

If you know the questions are coming, practice them.

This goes for any kind of scenario. Got to give a talk? Practice it. Going for a job interview? ‘Why should we hire you?’.

I practiced the exact questions she asked with my brother before the interview. I had a head start.


B) Get good at something

Being confident is being good at something.

If you’ve got some skills, own them. So you hear someone is looking for a few art designs, and you can draw. ‘Hey I can draw up a few things for you.’ Will it work all the time? Probably not. But at least you put it out there.

I’d been practicing understanding people for the past four years driving Uber and working at Apple. And I was good at it. So I told her. It’s easy to be charismatic about something you’re good at.


C) Practice again

This one is important enough to list twice. You don’t get good at something without practice. And practice usually involves being bad at something for a period of time.

It’s normal to lack confidence when you first start. But over time, your skills will improve and your confidence will begin to grow.


D) Tune the voice in your head to suit the conversation

There’s always that voice. The one telling you you should say something. Or telling you to go and talk to that girl. It won’t always be the right words. But the nervous energy will be there. Shape the energy to match the scenario.

I had no idea where the co-pilot strategy came from. The nervous energy must’ve sent it out. So I ran with it. And the subconscious took over.

There’s no way to get this to happen except to keep showing up. And learn how to use the energy when it arrives.

In the meantime, better to practice what you need to say or the skill you’re working on.

I think I would’ve won Survivor if I got on.

If you manage to get on, use the co-pilot strategy. Tell me how it goes.


Confidence comes in many forms

What’s your name?


Hey Sara, I’m Charlie. I’m your ward doctor.

Sara didn’t say anything.

You know why you’re here right?


We’re gonna work together on this. You’re going to get better. Is it okay if I ask you some questions?


When did you first notice something was wrong?

Every day for the past 8-years.

When did you get pregnant?

Two years ago.

Do you know who the father is?


Were you using whilst you were pregnant?

I don’t know.

How did you get here?

I brought myself in.


Sara didn’t respond. She was facing the other way.


Sara, it’s okay if you don’t want to talk, I can come back tomorrow.

Sara turned around.

My daughter doesn’t deserve a mother like me.

What kind of mother does she deserve?

I don’t know.

Well, you’ve made the right choice being here.

Sara looked at Charlie. She had tears in her eyes but her lips formed a nervous smile.

It’s easy to be confident when things are going well.

You’ve got a good job, a happy relationship, buying food isn’t a problem.

But what about when things aren’t going so well?

A confident person doesn’t always mean the well-dressed guy walking into the room with his head held high.

It’s also the person who hasn’t been through the best of circumstances but still takes it upon themselves to make a change.

Sara decided to make a change.


How much math do you need to start learning machine learning or deep learning?

‘I’m studying artificial intelligence.’

‘What?’ my Uber passenger asked, ‘is that like aliens?’

‘It’s more like a combination of math, statistics and programming.’

‘You’ve lost me.’

I didn’t really want to go back to university so I made my own Artificial Intelligence Masters Degree using online courses. I drove Uber on the weekends for 9-months to pay for my studies.

Now 7-months into being a machine learning engineer, I’m still working through it, along with plenty of other online learning resources.

My first line of Python was 3 weeks before starting Udacity’s Deep Learning Nanodegree.

I’d signed up and paid the course fees but I was scared of failing so I emailed Udacity support asking if I could withdraw my payment and enrol at a later date.

Screen Shot 2018-11-23 at 9.15.03 pm.png

I didn’t end up withdrawing my payment.

For 3/4 of the projects, I needed an extension. But I still managed to graduate on time.

The main challenge for me was the programming, not the math.

But to learn the math knowledge I did need, I used Khan Academy.


I was learning on the fly. Every time a concept came up I didn’t know about, I’d spend the next couple of hours learning whatever I could. Most of the time, I bounced between Stack Overflow, Khan Academy and various machine learning blogs.

How much math do you need?

It depends on your goals.

If you want to start implementing deep learning models and achieving some incredible results, I’d argue programming and statistics knowledge are more important than pure math.

However, if you want to pursue deep learning or machine learning research, say, in the form of a PhD, you’ll want a strong math foundation.

The math topics I listed above take years, even decades to fully comprehend. But thanks to deep learning and machine learning frameworks such as Keras and TensorFlow, you can start replicating state of the art deep learning results with as little as a few weeks of Python experience.

The thing with math is, it’s never going away. Math is the language of nature. It’s hard to go wrong brushing up on your math skills.

But if the math is holding you back from jumping in and trying machine learning or deep learning, don’t let it.

A fisherman doesn’t learn how to catch every single fish before he goes fishing. He practices one fish at a time.

The same goes for learning. Rather than trying to learning everything before you start, learn by doing, learn what you need, when you need.