Collection of materials created by the SAAS Education Committee for the purpose of instructing the Career Exploration Committee. Hosted by and maintained by the Student Association for Applied Statistics (SAAS).
Each semester in Career Exploration, we cover a wide breadth of topics. This semester, we go over:
- Intro to Datahub and Jupyter
- Python
- Numpy/Pandas
- Visualizations
- Intro to Linear Algebra and Linear Regression
- Intro to Machine Learning
- The Bias Variance Tradeoff, Regularization
- Kaggle 1 Data Cleaning and Exploratory Data Analysis
- Kaggle 2 Decision Trees, Random Forest, Boosting
- Kaggle 3 Neural Networks
- Kaggle 4 Recap
- Make sure you are in the slack workspace, navigate to the cx-sp20 channel
- Download the LectureX.zip file\n",
- Open datahub at http://datahub.berkeley.edu/ and log in with your berkeley account
- Click upload at the top right
- Upload LectureX.zip (X represents the lecture number, for example Lecture1.zip)
- Select 'new' at the top right of the datahub screen, and select terminal from the drop down
- Enter unzip LectureX.zip
unzip LectureX.zip
- Open the LectureX folder and open the ipynb file inside the LectureX folder
Our main source of file sharing will be uploading to slack. Remember to upload the entire zip file to Datahub and unzip.