Hi 👋

This is my personal learning record for Data100-Fall-2021 of UC-Berkeley.

The official website: https://ds100.org/fa21/.

Resources

All materials can be found on this offical page: https://ds100.org/fa21/

Labs

• Lab01. Prerequisite Coding
• Lab02. Pandas
• Lab03. Data cleaning and Visualization
• Lab04. SQL
• Lab05. Transformations and SQL
• Lab06. Modeling, Summary Statistics, and Loss Functions
• Lab07. Simple Linear Regression
• Lab08. Multiple Linear Regression & Feature Engineering
• Lab09. Content Review
• Lab10. Cross-Validation and Regularization
• Lab11. PCA
• Lab12. Climate Data
• Lab13. Logistic Regression
• Lab14. Decision Trees & Random Forests
• Lab15. Clustering

Hws

• Hw02. Sampling Error and Bias
• Hw03. Food Safety
• Hw04. Tweets
• Hw05. SQL
• Hw06. Bike Sharing
• Hw08. Housing I
• Hw09. Housing II
• Hw10. PCA
• Hw11. Gradient Descent and Logistic Regression
• Hw12. Spam & Ham I
• Hw14. Taxis

Projects

• COVID Part I
• COVID Part II

Highlights

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• pandas 👍 basics and tricks
• Data visualization 👍 matplotlib and seaborn mainly

Looking for answers for other cs-courses ?

🤗 Welcome to check my repo cs-courses.

Join me and enjoy the journey 🚀