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- 01 - Jupyter Notebooks
- 02 - Introduction to Anaconda and Conda
- 03 - Intro to Pandas
- 04 - Examining Pandas DataFrame contents
- 05 - Query a pandas Dataframe
- 06 - CSV Files and Jupyter Notebooks
- 07 - Read and write CSV files from pandas DataFrames
- 08 - Removing and splitting DataFrame columns
- 09 - Handling duplicates and rows with missing values
- 10 - Splitting test and training data with scikit-learn
- 11 - Train a linear regression model with scikit-learn
- 12 - Testing a model
- 13 - Evaluating accuracy of a model using calculations
- 14 - NumPy vs Pandas
- 15 - Visualizing data with Matplotlib
- Slides
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