Observing the June ML session was an extremely valuable experience for refining my machine learning and collaboration skills. I have gained a lot of practical experience in implementing machine learning algorithms such as RandomForestClassifiers and PCA and also gained some knowledge in Natural Language Processing. Furthermore, applying these algorithms independently on datasets has improved my proficiency in Python by discovering the use of newer libraries. I have also gained more experience in data processing by implementing a web scraper using Beautiful Soup and storing in pickle files after processing the data for further use.
I really enjoyed participating in weekly team meetings and listening to a variety of ideas to complete a single task. These meeting helped me learn professional behavior when it comes to working on a programming project and how to value each member’s contributions to an idea. Having members ranging from high school students to different levels of college students led to a supportive team environment where the more experienced programmers guided others with their knowledge while being open to ideas from others. During the past month, I have also gained experience in using collaborative tools such a Google Colab and Github which might be even more popular during the remaining time of this pandemic.
Highlights:
1- Weekly meetings including interactive and real-time coding sessions for the recommender system.
2- Working independently on implementing scraping scripts to collect data from various forms using Beautiful Soup.
3-Learning about newer models such and BERT model and TF-IDF embeddings for the recommender system.
Meetings:
I have been a regular participant of weekly meetings for which I received an invite. Due to a major difference in timezone, I have been watching recordings of webinars conducted by industry professionals.
Goals:
I am very excited and really hoping to be a participant in the July session to utilize the knowledge I have gained so far and get a better hands-on programming experience.