Machine Learning Resources

I have decided to a plunge at learning Artificial Intelligence and Machine Learning over the course of time. I have planned to create a series of blog posts on my progress and will be posting about my learning on this blog.

One of the issues when learning a new technology or topic is finding the correct resources. In this blog post, I will be consolidating the resources that I will be using for the learning process. I have been scrapping the web and looking for advice to start learning, but the only way to learn is to get started, hence today is day 0. The building block of AI/ML is mathematics and more specifically Linear Algebra (Dealing with Matrices). I have taken a course of Linear Algebra back in school and college, but I will still need to get my memory refreshed and for this I will be using courseware by MIT - 18.06 Linear Algebra. Previously, I have book-marked a lot of resources, but like everyone else once a link goes in to Bookmarks folder, there is no coming back, and this blog will serve me a good reminder of resources as well.

Once you are familiar with Matrices, it is a good time to get started with machine learning. One advice I keep hearing over and over again from lots of people is to do Andrew Ng’s Course on Machine Learning. The course is supposed to begin on Jan 25,2016 and would be running till April, 2016. I would be doing this course and alongside exploring other courses as well. Another online course which is recommended is Machine Learning Course by Udacity.

The above resources will help you get started with basic machine learning knowledge. I have to agree, it is easier to find ML resources than AI resources. The best open resources for AI is produced by MIT. Since, I’m more inclined towards learning AI as I would be using a lot of it in my day to day work, I’m planning to release blog posts more on AI. The course which I’m planning to use for learning AI from MIT - Artifical Intelligence. Most recommended read for learning AI is Artificial Intelligence: A Modern Approach. Peter Norvig is Director of Research at Google and is responsible for a lot of the AI produced at Google. His articles are a must read by anyone who programs a computer.

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