Machine Learning - Level 1 Module 3 - Lael Davis

Technical Area:

  • Knowing about different classification models
  • Understand about loading data into CSV and JSON files in order to be formatted for ML algorithms
  • Understand about web scraping/crawling and how that data can be used with different metrics


  • Google Colab
  • VSCode
  • Numpy/Pandas
  • Scikitlearn

Soft skills:

  • Learned how to collaborate with teammates and come to a cohesive decision
  • Learned a lot through reading articles and watching videos to further understand the material


  • Was able to clean my data successfully
  • Able to load data into a .csv file and .json
  • Learned about some of the classification modules
  • Came more comfortable understanding VSCode’s lightweight platform


  • Cleaned data correctly
  • Understood Bag of Words
  • Understood the cosine similarity and the distance metric which was early exposed in the first module

Hurdles/Problem Faced:

  • Small bugs and errors that may have taken more time then I’d like
  • Steepness of material to get through. Learned from Colin that our own implementation is better and more useful especially in the long run, rather than copying/learning from a template
  • Need to work on categorizing and formatting the data to get ready for the recommender system