Machine Learning Level 1 Module 3 pt 1 Self Assessment

Technical areas:

• Learned the basics of EDA.

• Learned how to create , word clouds, frequency plots, and bigrams, with matplotlib and Wordcloud.

• learned how to vectorize data and built a simple classifier using TF-IDF in sklearn. Tools: Selenium Webdriver, Numpy ,Pandas ,Matplotlib, Scikit, Wordcloud, NLTK, requests, gensim

Soft skills:

• I participated in our teams first group presentation, and I was in charge of presenting the current challenges in implementing our classifier, and where we want to see the project in the future.

• I helped schedule the prep for the presentation and distribute the presentation workload, and in the process got to meet and work with some of my peers, as well as the project lead and technical lead, very closely.

• We received a lot of useful feedback and tips from Sarah and Colin on effective communication using data, as well as where we can improve our classifier.


• Caleb from our team discovered our forum of choice for which we plan to build the recommender system; Drowned in sound. Our team also individually scraped/conducted EDA on the myPaint and Flowster forums.

• I learned how TF-IDF and logistic regression work. I have to understand naïve Bayes classifiers and BERT next.