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A few exercises in python to understand the basics of Machine Learning. This functions as a tutorial.

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Open Sessions

This repository contains all the notebooks that were used in the Open Sessions organized by fuse|ai. Our sessions were structured so that any newcomer with little to no programming experience would be able to understand how and why Machine Learning is used to solve problems in various sectors. Currently, the sessions have covered the following topics in order:

  1. Python basics, Object-Oriented Programming foundations, NumPy (Aayush Poudel)
  2. Data Manipulation with Pandas and Visualization with Matplotlib (Krishna Pandey)
  3. Regression tasks (Aayush Poudel)
  4. Classification and Ensemble tasks (Aayush Poudel)
  5. Unsupervised Learning (Suraj Regmi)
  6. Deep Learning (Kshitiz Rimal)

The notebooks and compilation of resources here are provided for anyone to use not as a comprehensive course but as a foundation for their further learning. The goal of the series has been to make the participants actively involved in the process of self-learning.

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A few exercises in python to understand the basics of Machine Learning. This functions as a tutorial.

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