Assessment 1
What I Learned
Technical
- Web Scraping with Beautiful Soup
- Machine Learning Tutorials
- Data Cleaning & EDA
Tools
- Github
- Slack
- Asana
- Jupyter
Soft Skills
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
Overview:
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:
- Technical-BERT,Web scraping , Topic modeling, Text pre processing
- Tools-BERT,Text Classifiers,pytorch
- Soft Skills-Communication,Team work
Three Achievement Highlights:
- Learned and implemented web scraping using Beautiful_soup
- Pre processes the text and utilized text classifiers to predict tags
- 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