Harrisj1j - Machine Learning (Level 1) Pathway

Self-Assessment for Machine learning Module 1

Technical Aspect:

  1. Get familiar with the machine learning workflow and other programs as apart of of module.
  2. Go over the whole process for building the recommender system, and more details for project expectations.
  3. Grasp a basic understanding of the software used for this internship.


  • Pytorch
  • Python
  • BeautifulSoup
  • Selenium

Soft Skills:

  1. Practice communication and interaction with group members.
  2. Practice using the stemaway interface.


  1. Setup all coding environments as a part of this project.
  2. Think deeper into the Machine learning workflow and grasping a better understanding of the project.
  3. Gained a better understanding of beautiful soup and selenium as a direct result of the first module’s content.

Self-Assessment for Module 2:

Things that I learned

Technical Area:

  • Utilized web scraping tools to gather data from different websites.
  • Accesed different files (mainly csv) and how to scraped data from them
  • Compared scraped data obtained from sites

Soft Skills:

  • Utilized jupyter notebooks & am becoming more comfortable using it
  • Developed familiarity with scraping data from the sites


  • Successfully scraped data from one of the forums
  • Successfully scraped data from a simpler website after Successfully doing so from a forum
  • Cleaned and pre-procssed data

Tasks Completed:

  • Performed analysis of data obtained and of course scraped the data.

Self-Assessments Module 3:

Technical Area

Web scraping of forum data

Python usage increased



Soft Skills

I learned teamwork by asking for help when I began to scrape the forum data. I used the help I got to proceed with scraping and exporting data.


Loaded scraped data and exported it in an excel file.

Explored scraped data to gain insights.

Visualized the data in excel tabs.


I got stuck while trying to scrape my category from the car forum. Eventually, after trial and error, I was able to figure out what to do and proceeded to explore the data.

Self Assessment for Module 4:

Technical Area:

  • Learned how to train BERT
  • Was able to combine various models like BERT with other models to assess their overall effectiveness and their accuracy.
  • Learned how BERT operates and how it can function


  • Simple Transformers
  • Jupiter Notebook *Pytorch

Achievement Highlights:

  • Was able to train various models and see what their relative efficiencies were.
  • Tried using different types of data, such as cleaned and not cleaned, to see which one was more effective in producing results (and again overall accuracy).
  • Tried to dock the ML App with models


  • As the modules became progressively more complex, it became a bit harder to understand the “meat” of the modules, so having a better understanding of machine learning in its entirety is a plus. I had a lot of trouble at first, but I was eventually able to obtain some of the knowledge I needed to complete this module’s tasks…