Machine Learning

Table of contents 👇

1. Intro to Machine Learning

Learn the core ideas in machine learning, and build your first models.

👉 https://www.kaggle.com/learn/intro-to-machine-learning

2. Intermediate Machine Learning

Handle missing values, non-numeric values, data leakage, and more.

👉 https://www.kaggle.com/learn/intermediate-machine-learning

3. Machine Learning with Python

You'll use the TensorFlow framework to build several neural networks.

You'll also dive into neural networks, and learn the principles behind how deep, recurrent, and convolutional neural networks work.

👉 https://www.freecodecamp.org/learn/machine-learning-with-python/

4. Machine Learning Explainability

Extract human-understandable insights from any model.

👉 https://www.kaggle.com/learn/machine-learning-explainability

5. Machine Learning Time Series

Apply machine learning to real-world forecasting tasks.

👉 https://www.kaggle.com/learn/time-series

6. Machine Learning Specialization

Break Into AI with Machine Learning Specialization. Master fundamental AI concepts and develop practical machine learning skills in this beginner-friendly 3-course program.

👉 https://www.coursera.org/specializations/machine-learning-introduction

7. Machine Learning with Python: Zero to GBMs

This course is a practical and beginner-friendly introduction to supervised machine learning, decision trees, and gradient boosting using Python.

👉 https://jovian.com/learn/machine-learning-with-python-zero-to-gbms