This course focuses on one of the main branches of Machine Learning that is Supervised Learning in Python. If you are not familiar with Python, there is nothing to worry about because the Lectures comprising the Python Libraries will train you enough and will make you comfortable with the programming language.

The course is divided into two sections, in the first section, you will be having lectures about Python and the fundamental libraries like Numpy, Pandas, Seaborn, Scikit-Learn and Tensorflow that are necessary for one to be familiar with before putting his hands-on Supervised Machine Learning.

Then is the Supervised Learning part, which basically comprises three main chapters Regression, Classification, and Deep Learning, each chapter is thoroughly explained, both theoretically and experimentally.

During all of these lectures, we’ll be learning how to use the different machine learning algorithms to create some mind-blowing modules of Machine Learning, and at the end of the course, you’ll be trained enough that you would be able to develop you own Recognitions Systems and Prediction Models and many more.

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