Self assessment 3

Full Session Assessment:

Concise overview of things learned. Break it up into Technical Area, Tools, Soft Skills:

Technical : 1) Web scraping, 2) Data organizing and cleaning, 3) Data feeding into BERT and doing classification

Tools :

1 ) Slack, 2) GitHub, 3) Python (pandas library) , 4) Asana, 5) DistilBERT

Soft Skills : Communication and team collaboration.

Three achievement highlights:

  1. Successfully scraped a category from Amazon forum website.
  2. Used pandas data frame to process data
  3. Implemented DistBert and analysis like logistic regression, random forest, etc.

List of meetings/training attended including social team events:

Team Meetings: All team meetings and final project presentation

Training Sessions/Webinars: attended Git Webinar. Watched the recordings of other webinars like NLP, Python training, etc.

Detailed statement of tasks done. State each task, hurdles faced if any and how you solved the hurdle. You need to clearly mark whether the hurdles were solved with the help of training webinars, some help from project leads or significant help from project leads.

Task 1: Set up Slack, Gsuit, Github, Asana

  • Task 1 Hurdles: Nothing much. Got help from the leads.

Task 2: Used Salenium and Beautiful soup for data Scraping.

  • Task 2 Hurdles: It was my first time scraping, so faced some trouble extracting informations out of the webpage webpage. Got lot of resources from the team 7 group and figured the task out.

Task 3: Data cleaning and processing

  • Task 3 Hurdles: Had no experience on NLP or BERT, but with teammate collaboration and help from the leads, successfully cleaned the data and processed it. It was a bit hard to grasp, but given enough time, was successful doing this task.

Task 4: Did classification algorithm by linear regression, random forest. Implemented DistBert

  • Task 4 Hurdles: Hurdle as well as major learning during this task was using several classification techniques like linear regression, random forest, neural network. Although neural network was not used, grasped some good idea about it while searching about classification algorithms. Used the classifiers as tools and got an idea about parameters to tune models.