Whether you are teacher, student, computer scientist, or proficient machine learning programmer, there are many times where having a solid reference library on the topic can save you a lot of time and help you to prepare material for your next lecture, article, even job interview. Machine learning algorithms and lately, deep learning, have in fact demonstrated excellent results and produced many breakthroughs in computer science. This is revolutionising many fields, including healthcare where medical records, medical images, and other patient-specific information are combined with advanced machine learning approaches to create advanced algorithms capable of performing high levels of data mining and leveraging patient treatment. That being said, there is a lot of hype about Machine Learning, Artificial Intelligence (A.I), wrong expectations about what A.I is, and what it can actually do. While the Internet is full with resources about the topic, there is nothing better than learning from leading researchers and educators in the topic. This motivated me to create a list of recommended books from different authors, who also provide a different view and focus to the topic, as well as describing challenges and future opportunities.

So here it is, my list of top seven books about machine/deep learning that I’d recommend you to definitely check out. This list includes general purpose books about machine and deep learning, as well as more specific ones focusing on machine and deep learning for medical imaging. Some very good ones focusing on implementational aspects with Python and Tensorflow, for those readers who look for practical examples and more hands-on focused learning.

I hope you like. Feel free to use the links below to know more details, and happy reading!