I took up a course on Git recently and thought of sharing what all I learned. No, I’m not promoting any course. It is always said that if you can teach it to others, then you’ve mastered the concept. So here I go telling you every bit of Git. I will divide the concepts into multiple articles so that it doesn’t seem too intimidating to the newbies. If you haven’t worked in terminal/command prompt before, I might also help you learn that.

While Gradient Descent isn’t traditionally thought of as a machine-learning algorithm, understanding gradient descent is vital* *to understanding how many machine learning algorithms work and are optimized. Understanding Gradient Descent might require a brief knowledge of Calculus, but I have tried my best to keep it as simple as possible.

With the rise of machine learning frameworks, we can now train classifiers with just a few lines of code. For traditional machine learning applications (in case you’re wondering, Deep Learning is the not-so traditional thing I’m talking about), the library scikit-learn is very widely used. It’s very user friendly, comes with a lot of hyper-parameters to alter in case we don’t get a decent accuracy.