Useful Resources


Recommended Online Courses


Most of us professionals have very little time and stamina to read through books. We would always prefer to go through some videos and learn the subject quickly. Here are some of the online courses that I found useful.

We have many sources of online video tutorials. Coursera, Udacity, edX, Udemy, Edureka are the most popular. Each of them have good set of tutorials on most subjects that one could think of. But when it comes to machine learning, nobody can beat Coursera, that is headed by Andrew Ng himself.

Useful Reference Books


Tutorials and blogs are great for an introduction to the subject and to keep in touch with the latest developments. But if you want to go deeper and master it inside-out, you have no alternative to books. Here are some of the useful text books and cookbooks that can help you master the subject.

Text Books


Textbooks are required to give a thorough introduction to a subject, elaborating on all the fundamental concepts. Here are some that I found very useful.

Cook Books


Text Books give us a good understanding of the subject. But, often it helps to get some ready solutions to common problems. That helps us from re-inventing the wheel. The cookbooks help us with that. Here are some that can help us in that.

Light Read


Some of the great authors have contributed to the literature. These may not directly help you understand the technical aspects of the subject. But they will surely help broaden your perspective.

Github Repositories


Github is the home of creativity. Techies from all over the world have deposited their creations into this ocean of code. If one can search for it, almost all problems that we face already have a solution on Github. Here are some of the repositories on Github that I found useful. This list will continue to grow as I find more and more of these.

Significant Research Papers


There is no other way to keep up with the latest trends in the developments in any domain. Research papers help us understand the sequence and basis of developments over the years. Below are some of the important research papers published over the last few years. Some of them mark important milestones in the development. Others form a good overview of the developments around the time. Anyone interested in a deeper understanding of the subject will surely want to read through them.

Image Processing


Speech Processing


Deep Learning Models


Optimization


Unsupervised Learning


Recurrent Neural Networks


Neural Machine Tuning


Reinforcement Learning


Deep Transfer Learning / Lifelong Learning


One Shot Deep Learning


Object Detection