Machine learning get started

HOWTO: Get Started With Machine Learning! (4 Tips)

Do you want to educate yourself more on machine learning? In this post I will give you some pointers to get started on either the technical, or the philosophical side!

So you want to know more about machine learning, and how to get started?
Maybe you want to get into the field of technical artificial intelligence, or learn more about the current state of A.I. philosophy.

In this post I will give you some invaluable pointers to resources you can use today to get a better grip on this new and exciting field of research that is taking the world by storm.

Whether you are a programmer, data scientist, mathematician, or in any other way interested in machine learning, there should be something in here for all of you.

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1. Books

Nothing beats a traditional good book about a subject, and even though it may be old school compared to the other tips I will provide after, there is something to be said for the amount of time and level of detail to goes into the writing of a book on a subject.

In my opinion, a book does not only provide the deepest knowledge laid out on subject, but owning a physical object to surround yourself with also helps you stay inspired on your quest to learn a new skill.

Here are a few that I recommend.

Programming Collective Intelligence 

Considered an esssential book to start machine learning. A lot of data scientists recommend this one, and many claim to have read it multiple times.

Machine Learning for Hackers

This is a great book if you are into R, or are planning to get into R. A great book to start your machine learning journey, and learn one of the essential tools for data science.

Machine Learning by Tom M Mitchell

A great book which does not focus on any one programming language, and makes it easy to understand the underlying theorems that are discussed within its pages.

Artificial Intelligence: A Modern Approach

Peter Norvig's carries quite some weight in his field, and his teaching style is one that must be experienced at least once in your life, after which you can probably not do without it.
This book is best suited for beginners, though it covers many subjects from beginner to advanced. Basically, if you can think of a problem you want A.I. to solve, this book will get you started.

Artificial Intelligence for Humans

This one requires quite a good understanding of math before you get started, and is filled with all the equations your heart can desire.

Artificial Intelligence: A New Synthesis

A real challenge for the mind, and great if you are a bit more advanced. I found it especially great to learn more about genetic programming.

The Emotion Machine: Commonsense Thinking, Artificial Intelligence and the Future of Human Mind

A truly amazing read to learn more about how the human mind works. There is some truly ground breaking research held within these pages.

2. YouTube

If you are not learning anything from YouTube, in my not so humble opinion, you are doing it wrong!

There is practically and endless supply of amazing teachers on there, teaching all kinds of subjects with highly qualified credentials, and yes: even on machine learning!

Here is a list of my personal favorites, which I highly recommend.

Siraj Raval

Siraj bursted onto YouTube with a great energy and quickly established himself as a wealth of information on machine learning. His teaching style is dynamic and very engaging, and he is extremely knowlegable. I am pretty sure he is the only one in the world right now doing freestyle raps on the topic of machine learning.

He has also set up a great slack channel, where you can connect with other people interested in machine learning and artificial intelligence.

Robert Miles

Robert is my favorite person to watch when I get more into the philosofical side of artificial intelligence, and when I want to think about more futuristic concepts and ideas. I used to watch him when he was featured on the Computerphile channel, but he has since started his own YouTube channel.
He has stated that he will probably start diving a bit deeper into the technical side as well, and I have heard him say he may even go over research papers, which would be truly awesome, as his delivery is very clear and full of depth.

Since his videos are a bit scattered over these two channels I have created a playlist with all his existing content, which I will keep curating as new videos come out.

3. Research Papers

If you are already a bit more advanced in machine learning, or you have put in the time through the book and YouTube recommendations I have provided, you can start diving into research papers.

This is where you can find the truly cutting edge of the technology as it stands today, and best of all, it is all published for you to find, experiment with, and improve upon.

Here are a few places where you can keep up to date with the latest publications.

Google Scholar

Journal of Machine Learning Research (JMLR)

Awesome - Most Cited Deep Learning Papers

4. Communities

I have already mentioned the Slack channel that Siraj Raval has set up, which is a great and vibrant community where you can connect with other people interested in machine learning.

You can find people with all kinds of skill levels there, and many of them are looking to collaborate on projects.

Here are a few more communities you may be interested in.

Kaggle

/r/artificial

Google+ Artificial Intelligence

Facebook Artificial Intelligence

Facebook Artificial Intelligence & Deep Learning

Facebook Data Mining / Machine Learning / AI

Bonus Suggestions

As soon as I posted this on social media, one Reddit commenter made a few other great suggestions, so I will maintain them in this section.

el_ryu on Reddit suggested:

As for YouTube, I´d recommend instead Geoffrey Hinton (the godfather of deep learning, and a great lecturer): https://www.youtube.com/watch?v=cbeTc-Urqak&list=PLoRl3Ht4JOcdU872GhiYWf6jwrk_SNhz9

And if you have time for more, one of the fathers of Coursera, Andrew Ng, has an awesome course on the topic in that platform: https://www.coursera.org/learn/machine-learning

If you don´t want to get that technically deep, and just want to play a bit with machine learning, try the tensorflow playground: http://playground.tensorflow.org or my chatbot authoring tool: https://mybot.be

Follow me on social media to get updates and discuss A.I., and I have recently created a slack team to see if people are interested to forming a little A.I. community,
Twitter  : @ApeMachineGames
Slack    : join the team
facebook : person / facebook group

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