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[SOML'21] Reference material, tutorial notebooks and other resources for Summer of ML, organised by AIMLC IITD.

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Summer-of-ML-2021

Resource Repository for AIMLC's Summer of ML 2021

The workshop is a month-long event with 5 major workshops across 3 weeks and a hackathon. Detailed schedule and other information of the series can be found on our website.


The amazing lineup of instructors for the workshops

We will start with the basic mathematics used in ML and intorduce some ML methods like Naive Bayes and Logistic Regression, that are built primarily on these mathematics. We will gradually move on to Deep Learning in the second week, with simple applications and a hands-on introduction to PyTorch. Finally, we will explore some important methods in Deep Learning like CNNs and RNNs. To test your understanding of the concepts you learned in the workshops, we will have a final 1-week hackathon.

To finish off with the series, we will take you through some more methods that are commonly used in Machine Learning. We will be covering topics ranging from clustering algorithms like K-means and GDA to expectation maximization techniques.


Events

  • Week 1 Mathematics and Basic Methods in ML

    • Day 1 Linear Algebra & Probability-Statistics
    • Day 2 Linear Regression and Multi-Variable Calculus
  • Week 2 Deep Learning & its Applications

  • Hackathon

  • Week 4 More Methods in Machine Learning

    • Day 5 More Methods in Machine Learning

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