Anindini Singh - Machine Learning Pathway - Self Assessment

Week: 07/ 28/ 2020

Overview of Things Learned: Web scraping, word embeddings, tf-idf, BERT

  • Technical Area: Natural Language Processing (NLP)
  • Tools: Github, Google Colab, NLP Libraries such as, Sselenium, Beautiful Soup, Word2Vec
  • Soft Skills: Articulating projects in presentations, collaborating virtually across different time zones

Meetings attended

  • 7/ 21/ 20
  • 7/ 24/ 20
  • 7/ 28/ 20
  • 8/ 4/ 20

Tasks Done

  • Designed a web scraping model for a discussion forum
  • Designed a BERT Model for classification tasks

Goals for the Upcoming Week

  • Generate a CSV file of the extracted data
  • Refine BERT model
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Week: 11/ 08/ 2020

Overview of Things Learned: BERT, DistilBert, and RoBERTa

Meetings Attended: 11/ 08/ 2020

Tasks Done:

  • Applied BERT model to web scraping data
  • Learned the differences between BERT, DistilBERT, and other such training models

Tools:

  • GitHub
  • Jupyter Notebook
  • Google Colab
  • Python

Achievements: Classified data scraped by the different groups in creating the BERT model

Goals for the Upcoming Week:

  • Improve the accuracy of BERT model
  • Implement its variations