Machine Learning - Level 1 Module 3 - Vibhu Krishnan

Overview of things learned:

  • Technical Area:
    • Learned how to clean data to work better for the model.
    • Learned how to use basic recommender systems and measure similarity.
    • Learned how to use various ML classification models to train a model and then test it.
  • Tools:
    • Google Colab
    • TensorFlow
    • Pandas
    • Random forest, Naive Bayes, Logistic Regression, SVM
  • Soft Skills:
    • Understood how to use recommender systems and classification models.
    • Learned how to improve models through repeated testing and changing certain things.

Achievement highlights:

  • Modified the data to better fit and improve the accuracy of the classification model.
  • Created a recommender system and measured similarity using cosine similarity.
  • Trained and tested various classification models to find the best one.

Tasks Completed:

  • Cleaned my data further and changed the text into word embeddings.
  • Created a recommender system to recommend a post based on liked posts using cosine similarity.
  • Trained multiple classification models and modified the data to improve the accuracy of them.
  • Tested the model by inputting sample data to test the model’s accuracy.