Machine Learning - Level 1 Module 1 - Dushyant

Overview of things learned:

  1. Technical Area:

    • Learned how web scraping is achieved by using Beautiful Soup

    • Learned about basic Machine Learning concepts and how different models are used

    • Gained an understanding of NLP and Recommender Systems

  2. Tools:

    • Google Colab

    • BeautifulSoup

    • Jupyter Notebooks

    • Git/GitHub

  3. Soft Skills:

    • Learned about the workflow of ML projects

    • Understood the importance of ethics in data mining

    • Learned how helpful forums and GitHub can be when learning new concepts

Achievement Highlights:

  • Practiced web scraping on some basic HTML pages and DiscourseHub community forums. The Beautiful Soup documentation was quite helpful

  • Properly set up my work environment and familiarized myself with all the tools

  • Learned about ML concepts and models from the webinars and other resources provided

Tasks:

  • Successfully prepared my workspace

  • Watched the webinars provided and learned about the concepts that will be needed for future modules

  • Learned and practiced web scraping using Beautiful Soup

  • Understood what a typical ML project’s workflow is

  • Read about NLP and how it is used today. I used a recommender system as an example to improve my understanding

Hurdles:

  • Training an ML model that classifies textual input as positive/negative sentiment was a bit difficult but I got a hang of it after looking at similar examples and learning about common bugs through forums.