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List of great books, podcasts, magazines, lectures, blogs & papers from the field of AI, Data Science, and Machine Learning.
Over the years, we machine learning engineers at Ximilar have gathered a lot of interesting ML/AI material from which we draw. I have chosen the best ones from podcasts to online courses that I recommend to listen to, read, or check out. Some of them are basic and introductory, others more advanced. However, all of them are high-quality ones made by the best people in the field and they are worth checking. If you are interested in the current progress of AI or you are just curious about what will be in the future then you are on the right page. AI will change all possible fields, whether it is physics, law, healthcare, cryptocurrencies, or retail and one should be prepared for what is to come…
If there is one medium that has become popular in recent years, it must be podcasts. Everyone is doing it right now – there are podcasts about sex, politics, tech, healthcare, brains, bicycles… and AI is not missing. But one of them stands out. It is a podcast by Lex Fridman. This MIT alumni is doing an incredible job by interviewing the top people from the field, famous people included (like Garry Kasparov or Elon Musk). Some episodes are more about science, physics, the mind, startups, and the future of humanity. The ideas presented in the podcast are just mind-blowing. The talks are deep but clever and it will take you some time to get through them.
The Turing test is a recursive test. The Turing test is a test on us. It is a test of whether people are intelligent enough to understand themselves.
Another great podcast is Brain Inspired by Paul Middlebrooks with interesting guests. It shows and discusses topics from Neuroscience and AI and how these fields are connected.
Life 3.0 by Max Tegmark – How will AI change healthcare, jobs, justice, or war? Max Tegmark is a professor at MIT who has written this provocative and engaging book about the future. He tries to answer a lot of questions like What is intelligence? Can a machine have a consciousness? Can we control AI? … This is a great introduction even for non-technical people.
Human Compatible by Stuart Russel is an important book that asks questions on how to coexist with intelligent AI in future.
AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee – A book about the incredible progress in AI in China.
Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron – Do you know how to code and would you like to start with some experiments? This book is not only about one of the most popular programming frameworks (TensorFlow) but also about modern techniques in machine learning and neural networks. You will code your first image recognition model and learn how to pre-process and analyze text.
Deep Learning for Coders with Fastai and PyTorch by Jeremy Howard and Sylvain Gugger – Another great book for coders. Code examples are in the PyTorch framework. Jeremy Howard is a famous researcher and developer in the AI community. His Fastai project helps millions of people to get into deep learning.
There are many more interesting books oriented for software developers like Deep Learning with Python by François Chollet. Looking for more hardcore books with math equations? Then try Deep Learning by MIT Press. If you are interested in classic approaches, then many university students will remember preparing for exams with Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig or Bishop’s Pattern Recognition and Machine Learning. (These two are a bit advanced and many topics are for a master’s or even PhD level.)
MIT Technology Review is a great magazine with the latest news and trends in technology and future innovations. The magazine covers also other interesting topics as biotechnology, blockchain, space, climate change, and more. There is a print or digital access option for you.
There are a lot of famous Scientists & Engineers & Entrepreneurs to follow. For example, often mentioned Jeremy Howard (fast.ai), Andrej Karpathy (Tesla AI), Yann LeCun (Facebook AI), Rachel Thomas (fast.ai, data ethics), Francois Chollet (Google), Fei-Fei Li (Stanford), Anima Anandkumar (Nvidia AI), Demis Hassabis (DeepMind), Geoffrey Hinton (Google), Eliezer Yudkowsky (AI Alignment), Ilya Sutskever (OpenAI) and more…
So you’ve read some books and articles and now you want to start digging a little deeper? Or do you want to become a Machine Learning Specialist? Then start with some online courses. Of course, you will need to learn a little bit about math before and get some basic programming skills. Online courses are a great option if you can’t study at university or you want to get knowledge at your own pace. Here are some of the courses that can serve you as the starting point:
You know how to code and you even know how to build your CNN? Or are you just simply interested in what is the future of the field and how companies are using AI? Check out some of the latest trends and SOTA approaches from the top research groups in the world. There are several giants like Apple, Facebook and Google pushing the AI boundaries:
There are also a lot of AI research labs located at top universities such as MIT, Stanford, or Berkeley.
We are always looking for high-quality content which is why some of the following articles can be a bit longer. AI is a complex field which is disrupting the way we live and do business:
A lot of things happened during the last few years, here are some research articles that pushed the boundaries of AI by a large margin ordered by date (since 2010):
Here is the hall of fame in complex Artificial Intelligence projects:
That is all for now. There are other great resource lists like the one from DeepMind, from which I got inspired. The list is divided by the level of the target audience – introductory, intermediate, and advanced. We will try to keep this post updated and if we find a gem, it will definitely appear here. There is much more material from which you can learn, but now it’s up to you to start your own machine-learning journey. We will try to keep this article updated with the latest news in Artificial Intelligence.
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