Harshavardhan - Machine Learning Pathway

Assessment 1

What I Learned


  • Web Scraping with Beautiful Soup
  • Machine Learning Tutorials
  • Data Cleaning & EDA


  • Github
  • Slack
  • Asana
  • Jupyter

Soft Skills

  • Teamwork
  • Networking

Three achievement highlights

  • Explored ML & Exploratory Data Analysis tutorials.
  • Created a web scraping script to collect data from a website.
  • Perform data cleaning and EDA to output clean csv file.

List of meeting/training sessions attended

  • STEMCast: Overview of ML and project
  • Git Webinar
  • Weekly Team meeting 06/8
  • Weekly Team meeting 06/15

Goals for upcoming weeks

  • Learn more about about text pre-processing,NLP & text classification.
  • Explore data visualization.

Assessment 2


What I learned last week:

Technical: Text analysis, word Embeddings, Basics of BERT, TF-IDF analysis
Tools: PyTorch, scikit-Learn library,BERT

Three Achievement highlight:

• Learned and implemented TF-IDF for pre-processing of text.
• Calculate Ter and inverse document frequency for different features.
• Gained knowledge on text classification using BERT.

Meetings/Training Attended:

Week 4 Team meeting
NLP webinar: STEMcast

Goals for upcoming week:

• Implementation of BERT model for topic modeling
• Try different models and more on NLP

Self Assessment-3
What I learned:

  1. Technical-BERT,Web scraping , Topic modeling, Text pre processing
  2. Tools-BERT,Text Classifiers,pytorch
  3. Soft Skills-Communication,Team work

Three Achievement Highlights:

  1. Learned and implemented web scraping using Beautiful_soup
  2. Pre processes the text and utilized text classifiers to predict tags
  3. Explored BERT and different models for classification.

List of Training/Meetings Attended:

-NLP webinars.
-Team’s weekly Meetings

Goals for the upcoming week:
-Consider Machine Learning as a potential career path