Ryanoh - Machine Learning (Level 1) Pathway

Module 1

Technical Area

  1. Learned how to import Beautiful Soup
  2. Familiarized with the concept of machine learning
  3. Watched videos relating to machine learning and Google Collabs.

Tools:

  1. Beautiful Soup
  2. Visual Studio Code
  3. Trello
  4. Discourse Forums (various types of discourse forums)

Soft Skills:

  1. Learned basics of web scraping

Achievement Highlights:

  1. Was able to communicate with the team members and set up Trello (selected team name)
  2. Familiarized myself with web scraping and discourse forums
  3. Prepared myself with necessary tools (was able to select the discourse forum with the team)

Module 2

Things Learned:

Technical Area:

1.I used google collaboratory to import Beautiful Soup and performed basic scraping of the website: https://forums.tapas.io/ 2. Learned how to inspect elements in details. 3. Performed basic scraping

Tools: Beautiful Soup, Google Collab

Softskills: Learned python and perfomred basic scraping with beautiful soup Achievement Highlights

1.successfully scraped elements 2. successfully set up for the module. 3. Familiarized with python .

Detailed statement of tasks completed:

  1. I was able to analyze various elements and scarped the website

Module 3

Technical

  1. Converted the scraped data to CSV file.
  2. Was able to train systems.
  3. Used various models to build recommender system.

Tools VS Studio CSV File Python -imported SKLearn, Pandas, etc

Soft Skills I had trouble using the program to import SK learn for various models.

Achievement Highlights 1.Trained models 2. Built a simple recommendation system 3. Made the data to csv file.

Detailed Statement

  1. I cleaned my csv file.
  2. Although it was not of high accuracy, it was still able to predict and recommend.
  3. I successfully got f1 value and other statistics.

Module 4

Technical

  1. Was able to train advnaced models like linear regression and BERT model.
  2. Was able to compare the performance of each model.
  3. Was able to improve performance of the models.

Tools VS Studio CSV File Python

Soft Skills

  1. I originally had to debug alot, due to complexity of each model.
  2. I was able to visualize the data
  3. I was able to build a recommender system as well as printing the performance of each model.

Achievement Highlights

  1. Used various advanced training models for recommenders.
  2. Was able to compare the efficiencies.
  3. Was able to visualize data into graphs.

Detailed Statement

  1. I orignally faced a lot of errors with the models, especially with importing libraries.
  2. I eventually figured out how to combine complex model with simple ML recommender.
  3. I performed basic data preprocessing