This is the code for "Intro to Statistics - Data Lit #2 by Siraj Raval on Youtube at School of AI.
Create a Jupyter notebook with a detailed Exploratory Data Analysis report of this lending club data. Make sure to use the 3 key statistical concepts i mentioned in the video (statistical features, probability distributions, and bayesian stats). Submit your github link in the comments section of the video. I'll give the winner a shoutout in a week!
- Random Forest with Randomized search CV -- 82.09
- Logistic Regression with Grid search CV -- 83.18
- Support Vector Machine with Grid search CV -- 82.50
- K Nearest Neighbors with Grid search CV -- 77.40
- Bagging with Base estimator as Random Forest -- 84.10
- Bagging with Base estimator as Logistic Regression -- 83.10
- AdaBoost Classifier ----- 83.60
- MultilLayer Perceptron Classifier ----- 83.40
Note: Check out our project report to find out why we used these algorithms.
- Programming Language: Python
- Libraries: Pandas, Scikit-learn, Matplotlib, Seaborn
- Visualization: plotly