ML Study Jam is a collective learning program helping community members to grow as ML practitioners. The idea is to go through basic ML concepts and share the knowledge in a community. By honing skills and enhancing capabilities, a beginner can start one’s journey to becoming an ML expert. 🤖 🚀

This track is a study program going through Kaggle Learn courses. The goal of these assignments is to cover the most essential skills rapidly. Such as how to use TensorFlow or Pandas and how to build your first Machine Learning model and participate in your first competition 👏 🎉.   

Kaggle is the world’s largest data science and machine learning community. It offers a no-setup, customizable Jupyter Notebooks environment, access to free GPUs, and a huge repository of community-published data & code.

"Intro to Machine Learning" is the first session of a series of 5 sessions :

1. Intro to Machine Learning
2. Intermediate Machine Learning
3. Intro to Deep Learning
4. Time Series 
5. NLP ( Bonus session )

In this first session, we are going to cover the content based on Kaggle's micro-course "Intro to Machine Learning":

1. How Models Work
2. Basic Data Exploration
3. Your First Machine Learning Model
4. Model Validation
5. Underfitting and Overfitting 
6. Random Forest
7. Machine Learning Competitions 

For more details, you can check it out below 👇

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

Requisites: 

1.  Have access to a Browser (preferably Google Chrome)

2. Sign up to Kaggle 

3. Eager to Learn !!! 

4. Have Completed the 🐼 Pandas microcourse