If you have any particular Machine Learning or Data Science problem you need consultation on, please mail at [email protected].
If you are just starting out with machine learning, I will share a list of resources to help you get started.
One of the major mistakes I did was I started learning without a proper base of mathematics. I know sometimes the mathematics get hard, but there are some great free resources to learn it. I highly recommend 3Blue1Brown’s videos.
The Essence of Calculus
Maths Behind Neural Network
Please check out all the other videos as well.
I also highly recommend Statquest with Josh Starmer. You can start with this playlist.
Basics of Machine Learning
Please check out all his other videos to understand the basics on which the machine learning stands. He explains things very lucidly.
I also recommend this freely available course from the Imperial College of London. This is also present as a course on Coursera.
Once you are more or less comfortable with the basic maths (you will never finish with maths, unless you are from a pure maths background), Andrew Ng’s course is considered to be the backbone of machine learning. It is not for absolute beginners, so make sure you have the basic understanding of the mathematics before you start with that.
Machine Learning – Classroom Lectures in Stanford
Machine Learning – Shorter video based e-teaching
Once you are done with this, I would be sorry to tell you that these methods, although the bases of machine learning, are almost obsolete now. They are used in part here and there, but the state of the art architecture keeps changing. To have a more customised discussion about your machine learning journey, please mail at [email protected]
If you are a seasoned machine learning engineer, then I am sharing some of the channels I love to follow to keep updated on the latest trend in papers.
Two Minute Papers
Please check out his other videos apart from the playlist I am sharing.
Please check out his other videos apart from the playlist I am just sharing
Kaggle Reading Group
Machine Learning Street Talk
Amazing podcasts with the host putting in a lot of effort in editing and trying to keep things understandable.
The list is extensive and I will continue adding more resources.