"# This is a Big ML CheatSheet both in Python & R" Projects & datsets included:
- Salary prediction using Linear Regression
- Future profit or revenue prediction using Multivariate Regression
- Salary Bluff or not prediction using Polynomial Regression, Support vector Regression, Decision Tree Regression & Random forest regression Note: Random Forest Regression will give the best results since its an ensemble of multiple decision trees but if you want to save computing power & computing time polynomial regression is better than decision tree regression.
- Purchasing Behaviour or purchasing likeliness Prediction using Logistic Regression, K Nearest Neighbors, SVM, Naive Bayes, Decision trees, Random Forests
- Mall customer clustering using K-Means Clustering & Heirarchical Clustering
- Market Basket Optimization using Eclat & Apriori algorithm for Association Rule miming
- Sentiment Analysis on Restaurant Reviews through NLP
- Customer Churn Prediction & Analysis using deep learning (NN) & XGBoost
- Cat & Dog Image Recognition using Convolutional Networks
Bonus Codes on:
- Dimensionality Reduction &
- Model Selection