Machine Learning Course Description

Machine Learning Course Description

Before you start, let me give you an overview of what this series has to offer you. Our machine learning course series comprises of the following sections:-

  1. ML Environment Setup and Overview
  2. Jupyter Notebook: The Ultimate Guide
  3. Numpy
  4. Pandas
  5. Matplotlib
  6. Seaborn
  7. Sklearn
  8. Linear Regression
  9. Logistic Regression
  10. Decision Tree
  11. Random Forest
  12. Support Vector Machine
  13. K Nearest Neighbours
  14. Naive Bayes
  15. Hyperparameter Optimization for Model Tuning

We will try to be on exact topics which i.e. we will not go so much deep or so much Shallow, we will try to be in middle, but we will not leave you out of any knowledge which may give you problems in your life journey. We assure you that we will always take it easy for you in the whole machine learning course.

These are the things that you’ll learn in the course. This course is designed to quickly get you started with ML so you can create projects that’ll help you level up your resume. Hope you’ll have fun learning throughout the course :). Bon Voyage.

Complete Machine Learning Course RoadMap Video

Credits to Daniel Bourke

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Author: Keerthana Buvaneshwaran