How to get started with Machine Learning

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Bunch of you asked me how to get started in machine learning.
So I thought I should make a video about it.

List of resources:
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Learn Python
Learn everything else about Python on the fly.

Learn ML (high-level intro)
+ at least 1 open-source project + 1 blog

Learn ML (middle-level intro)
Again code, code, code. Open-source on GitHub.

Start reading research papers and implement 1 paper from scratch.

Learn ML (pro)
Supplements:

Learn deep learning (pro)
(you'll find a good pdf in this GitHub repo)

BONUS TIPS:

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⌚️ Timetable:
0:00 ML and main obstacles to learning it
1:50 STEP1: Learn to code (in Python)
3:36 STEP2: Get a high-level intro to ML (Coursera)
4:43 How much time do I need to complete it?
5:05 Code your own project (GitHub, Medium)
8:26 STEP4: Read and implement research papers
10:00 STEP5: Get strong mathematical foundations
11:35 TIP1: Learn how to learn
12:04 TIP2: Learn only the tools you need
12:38 TIP3: Get into the output mode (code, blog)
12:58 TIP4: Focus (the field is too broad)
13:24 TIP5: Follow AI people on Twitter
13:37 TIP6: Watch Lex's AI podcast
13:52 Comment and subscribe

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💰 BECOME A PATREON OF THE AI EPIPHANY ❤️

If these videos, GitHub projects, and blogs help you,
consider helping me out by supporting me on Patreon!

Much love! ❤️

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💡 The AI Epiphany is a channel dedicated to simplifying the field of AI using creative visualizations and in general, a stronger focus on geometrical and visual intuition, rather than the algebraic and numerical "intuition".

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#machinelearning #learnmachinelearning #deeplearning

[TheAIEpiphany]

Hi folks! All of the links are in the description!

Here is the rough skeleton of the video.
1. Learn software engineering/coding in Python
2. Get a high-level overview of the field (Coursera)
3. Start to get deeper (fast.ai)
4. Start reading research papers and implement at least 1 paper from scratch
5. Get a sound maths foundations

Happy (deep) learning!

[kin_]

'embrace the suck' ahahah i swear this was the most important aspect of learning ML and reading research papers.

[dzimiks]

These tips are precious and pretty accurate. I really like how you try to explain in the best way and give us the best practices from the tech industry. Keep going!

[kaushiknath]

One of the best roadmaps i have come across while searching how to start ML. Thanks buddy

[salehsargolzaee]

I was lost in the learning process lately so bad, and it was really helpful; thank you.

[quant-trader-]

Man after hearing your very first advice, I know you know what you are talking about! I see so many bright "researchers" handicapped by their coding skills. Software engineering skills indeed should be ranked THE top skill to have if you ever want to be truly productive in any technical field, e.g., ML.

[aceleryful]

Dude, you are the best! I share your passion for passing on what I have learned, thanks!
Also, I appreciate the time you put into making these videos.
Also++, I can't believe this has so few views and likes.
Gracias pibe!

[tapiwamatsika]

I do agree with you on taking Mike's lessons, he is very good at making the language curve less bumpy

[NickWindham]

Great advice. You’ll hit 100k subscribers quickly. Keep up the great content

[greatfate]

you are the best thing that's ever happened to me. I miss you dreadfully

[OtRatsaphong]

Thanks for this roadmap and tips. Already starting a blog and planning my DL MVP

[danielqu]

thanks man, its really helpful.i have been learning these stuff for about five monthes now, starting with books like introduction to algorithm, probalistic machine learning byKevin Murphy', reinfocement learning by Sutton & Barto, and online course from Probabilistic Machine Learning by Philipp Hennig, and David silver's lecture i on reinforcement learning is excellent! as well the deep learning course lectured by other DeepMind researchers. and its great pleasure to read Petar Veličković's paper. iits encouraging to see that someone self taught can get into DeepMind. hopefully i can get somewhere one day

[marc-edwinrigaud]

Exactly what i was looking for. I did computer engineering in college, with a focus on ML, but havent used it since. And i really want to take my career in that direction. Thanks for this video, and all the resources

[inflamezish]

HI thanks man. I am getting started with Machine Learning. I found this video incredilby useful.

[fxtech-art]

Awesome ! i'm trying to find proper roadmap since few weeks..it was really frustrating as there so much material...and i can surely say this is the one.
thank you so much Aleksa✌

[hegerwalter]

Great that you can make a video on the side too. I remember editing my karate kata video, which took far more time than I thought that it would.

[quangluong]

Comment here to start following your advice from today. Thank you so much for the knowledge.

[kenkens]

This video is a holy grail. Thanks dude

[giuliaesposito]

Thank you very much for sharing your expertise with us.
Its huge act of generosity.

[lukasugar]

Bunch of useful stuff, even someone who is quite deep into ML can find a lot of useful information in this video. But I do have to disagree with your first statement, that in the School of Electrical Engineering in Belgrade there are no ML classes: prof. Predrag Tadic is doing a great job, he's teaching two ML courses and I highly recommend them to all students.