# Machine Learning Level 1 - Module 4 - Dushyant Chaudhary

**URL:** <http://staging.stemaway.com/t/machine-learning-level-1-module-4-dushyant-chaudhary/9108>\
**Category:** Machine Learning Pipeline (NLP) (CE) 2021\
**Created:** [July 31, 2021, 1:18pm UTC](http://staging.stemaway.com/t/machine-learning-level-1-module-4-dushyant-chaudhary/9108 "2021-07-31T13:18:23Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Dushyant](https://d3rzmptxz7fqzy.cloudfront.net/letter_avatar_proxy/v4/letter/d/41b3a3/32.png) [@Dushyant](http://staging.stemaway.com/u/Dushyant)\
**Post date:** [July 31, 2021, 1:18pm UTC](http://staging.stemaway.com/t/machine-learning-level-1-module-4-dushyant-chaudhary/9108/1 "2021-07-31T13:18:24Z")

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**Overview of things learned:**

1. Technical Area:

- Learned about advanced models like BERT, xlm, roberta, distilbert
- Learned how to use SimpleTransformers library in the model
- Gained an understanding of combining an advanced model (BERT) and a simple one (logistic regression)
- Used matplotlib to plot some graphs about the data and learned about balancing data

1. Tools:

- Jupyter Notebooks
- Google Colab
- SimpleTransformers
- Pandas, numpy, csv, matplotlib

1. Soft Skills:

- Enhanced my knowledge about advanced machine learning
- Collaborated with my teammates for presenting our work to our mentor
- Extensively used various online resources to debug my code

**Achievements:**

- Successfully created a recommender system that uses BERT and logistic regression to predict the category of a post (topic title and leading comment was input)
- Gained a decent understanding of advanced models like BERT, xlnet, roberta
- Understood what steps to take next for solving the problem of unbalanced data

**Challenges:**

- Running the model took a lot of time, and I had to debug it repeatedly
- The model takes up a lot of RAM, so it crashed a few times