Machine Learning- Level 1 Module 1- Shreya Vora

Technical:

  • I learned about recommender systems that have many different methods such as Content based method, Collaborative filtering method, and the Hybrid method
  • The importance of NLP in recommender systems as it helps with the pre-processing of data.
  • Data mining is really important and can be done using two different modes: APIs and and Web Scraping/Web Crawling
  • APIs are a large set of data that are given for different applications
  • Web Scraping is the method in which you can take data from one source
  • Web Crawling is the method in which data is taken from many different sources
  • Learned about new python libraries that helpful in web crawling that make it simpler like BeautifulSoup
  • Scrapy is an important tool that can be utilized to make Web Crawling easier and a lot more efficient

Tools:

  • Google Colab
  • Scrapy
  • Discourse
  • Python Libraries (BeautifulSoup)
  • GitHub

Soft Skills:

  • Continue learning more about Machine Learning and its webbing into NLP
  • Understanding different python libraries that are used for web crawling (looking and understanding the documentation)
  • Continue practicing Web crawling and scraping using python libraries
  • Continue to practice GitHub methods

Achievements:

  • Learned about different recommender systems
  • Revised python libraries and python basics
  • Got introduced to new mechanisms of data mining like APIs, web scraping, and web crawling/spiders

Tasks:

  • Understood the machine learning basics
  • I looked through the different python libraries such as BeautifulSoup
  • Understood the difference between Web Scraping and Web Crawling
  • Looked at videos to understand the basics of NLP
  • Set up a Google Colab
  • Understood the basics of logistic regression and linear regression