/data-science

CS M148: Intro to Data Science

Primary LanguageJupyter Notebook

CS M148 @ UCLA

Intro to Data Science

Topics Covered:
  1. Data Collection, Cleaning, Bias in the Data
  2. k-Nearest Neighbor (kNN), Linear Regression, Interpretations
  3. Multi & Poly Linear Regression
  4. Model Selection & Cross Validation
  5. Hypothesis Testing
  6. Regularization: Ridge & Lasso
  7. Logistic Regression, Interpretations
  8. Multi-Class Logistic Regression
  9. Data Summarization & Submodularity
  10. Submodular Maximization
  11. Model Interpretation
  12. Learning from Large Datasets
Tools Used:

Python, Jupyter, Numpy, Pandas, Matplotlib, Plotly, Sklearn