Wednesday

Hands-on with Python & Supervised Learning - Your 'Real' Coding Journey Begins

Unsupervised learning: A sneak peek. We’ll give you a taste of this fascinating world where machines discover patterns on their own.

Note: All the following files will become weblinks on the day of the class.

• Material for today will be shared during the class and/or posted here just before the class. 

  1. Google Slides: What did we learn yesterday?

  2. Learn how neural networks function by coding them in a Google Sheet and learn what 'weights' or 'parameters' do:

     • Google Slides Neural Networks  

     • and the corresponding Google Sheet: Understanding Neural Networks 

  3. Google Colab Notebooks:   

     • • Supervised Learning:

         • Classification - Perceptron for Digits Version 1  <<<<<<=============== Start from here

         • Classification - Perceptron for Digits Version 2

         • Classification - Perceptron for Digits Version 3

       • Numerical Data: Iris Flower using Decision Trees

       • Text Data: 

         • Sentiment Analysis Version 1  and the corresponding data: movie_data_reduced.xlsx

         • Sentiment Analysis Version 2  and the corresponding data: movie_data_reduced.xlsx (It allows you to write a review and get a rating!)

         • Sentiment Analysis Version 3 is the same as above but uses the FULL data, which it reads from a Google sheet. Accuracy of almost 90%.

         • Sentiment Analysis Version 4 is the same as above but uses 5 sentiments rather than 2 (coming soon!)

       • Images: SVM for Digits (Optional) 

     • Supervised Learning (Regression): 

       • Numerical Data - Weather Prediction 

     • Unsupervised Learning (Clustering): 

       • Numerical and Categorical Data: KMeans Clustering for Iris Flower

       • Images: KMeans Clustering for Digits