30 Top Videos

30 Top Videos, Tutorials & Courses on Machine Learning & Artificial Intelligence from 2016

30 Top Videos, Tutorials & Courses on Machine Learning & Artificial Intelligence from 2016
2016 has been the year of “Machine Learning and Deep Learning”. We have seen the likes of Google, Facebook, Amazon and many more come out in open and acknowledge the impact machine learning and deep learning had on their business.

Last week, I published top videos on deep learning from 2016. I was blown away by the response. I could understand the response to some degree – I found these videos extremely helpful. So, I decided to do a similar article on top videos on machine learning from 2016.

People often ask us “How should I get started with data science & machine learning?”

There can not be just one answer to this question. The anatomy of machine learning is quite vast. One needs to decide their own framework and time period to get comfortable with machine learning. Through this article, I want to help you reach that comfort zone.

In this article, I have compiled popular and most viewed machine learning videos, tutorials and courses from 2016. I want to help you to get started with machine learning and gain expertise building predictive models using machine learning. You are free to decide your own framework and time period to watch these videos. It is always advisable to take baby steps but feel free to mould it as per your wish.

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In order to help you, I have arranged the article and suggested a way to go through them. Hope you find it useful.

In this article, I have segregated the videos for beginner & advanced. The first section of the article will introduce you to machine learning basics and the underlying theory to make you get comfortable with the machine learning. If you are just getting started with machine learning then this section should be your first stop. Go through these videos one by one, and put the learning into practice with a practice problem.

For those who already have a basic understanding of machine learning, you should start with the advance machine learning videos. These videos will introduce you to various machine learning libraries, modeling techniques and other advanced concepts of machine learning. Once you are thorough understanding with advanced concepts of machine learning, try your hands on Black Friday practice problem.

After you have an understanding of how machine learning works, embark upon the next section on the applications of machine learning. These videos will blow your mind on how machine learning is changing the world. Find out how companies today are using machine learning to makes things simpler for us.

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In this video, Tetiana Ivanova shares her journey of becoming a data scientist in just 6 months. Participating in hackathons got her started with machine learning. If you have been wondering whether to go for analytics post-graduate program or become self-taught data science professional, you must watch this video. Tetiana shares her real life experience of making the career move, the hardships and truth behind the facade of a higher education. Either you are a beginner or someone transitioning his / her career to data science then I would recommend that you must watch this video. This video will leave you inspired.

In this course from Carnegie Mellon University, it will take you through basics of machine learning and statistical modeling. You will learn about parametric &  non-parametric regression, clustering, boosting, graphical methods, minimax theory, dimensionality reduction, etc. This course is best suited for students with a sound background in statistics & mathematics. Alongside, there are assignments & solution which would further improve your concepts. Feel free to skip the initial few minutes of the first video.

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This course on machine learning from the University of Waterloo will take you through machine learning basics and advanced concepts. It’s a conceptual course which will educate you on mathematical relations in ML algorithms. It has been taught by multiple professors including Shai Ben David, author of book Understanding machine learning.

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