Machine Learning Level 1 Module 2

Things that I learned

Technical Area:

  • Utilized web scraping tools to gather text data from websites. Additionally used the Tweepy API to gather text data
  • Pre-processed and cleaned the text data by removing tags, comments and mentions
  • Understood the process of verctorization of tweets and how words are represented as vectors
  • Used basic ML models like Logistic regression and naive bayes to find similar words
  • Employed a better neural network based approach for recommender systems
  • Compared performance of both methods using the results obtained

Soft Skills:

  • Improved usage of various python libraries and web scraping tools
  • Utilized jupyter notebooks
  • Developed familiarity with flask for web app deployement

Achievements:

  • Successfully scraped data from one of the forums provided
  • Successfully scraped data from a simpler website
  • Cleaned and pre-procssed data
  • Successfully employed classification algorithms

Tasks Completed:

  • Performed statistical analysis of data obtained
  • Was able to use classification algorithms. Also understood the algorithms through video tutorials

Link: https://github.com/harshita19244/classifiers/blob/main/preprocess.py