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Image Compression, Time Series Forecasting, Recommender System

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ml-assignment-2

Achieving 100/100 points

Task 1: Image Compression

  • Compressing images with PCA and reconstructing them
  • Finding the optimal number of components using threshold of explained variance
  • Building an image classifier of Logistic Regression
  • Compressing images, reducing number of colors with k-means clustering

Task 2: Time Series Forecasting

  • Checking if TS is stationary with ADF
  • Stationarizing the TS through differencing Vs. deseasonalization
  • Finding the hyperparameters for ARIMA model
  • Forecasting with ARIMA model

Task 3: Recommender System

  • Content-based recommender system
  • Collaborative filtering recommender system (Item-based)
  • Combining both into Hybrid recommender system

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