Module 1
Overview of things learned:
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Technical Area:
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Learned how web scraping is achieved by using Beautiful Soup
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Learned about basic Machine Learning concepts and how different models are used
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Gained an understanding of NLP and Recommender Systems
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Tools:
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Google Colab
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BeautifulSoup
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Jupyter Notebooks
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Git/GitHub
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Soft Skills:
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Learned about the workflow of ML projects
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Understood the importance of ethics in data mining
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Learned how helpful forums and GitHub can be when learning new concepts
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Achievement Highlights:
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Practiced web scraping on some basic HTML pages and DiscourseHub community forums. The Beautiful Soup documentation was quite helpful
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Properly set up my work environment and familiarized myself with all the tools
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Learned about ML concepts and models from the webinars and other resources provided
Tasks:
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Successfully prepared my workspace
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Watched the webinars provided and learned about the concepts that will be needed for future modules
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Learned and practiced web scraping using Beautiful Soup
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Understood what a typical ML project’s workflow is
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Read about NLP and how it is used today. I used a recommender system as an example to improve my understanding
Hurdles:
- Training an ML model that classifies textual input as positive/negative sentiment was a bit difficult but I got a hang of it after looking at similar examples and learning about common bugs through forums.