Machine Learning A-Z™: Hands-On Python & R In Data Science

Learn Various Algorithms and worked on different datasets to apply these Algorithm.

Algorithms :

Regression :

• Simple Linear Regression
• Multiple Linear Regression
• Polynomial Regression
• Support Vector Regression
• Decision Tree Regression
• Random Forest Regression

Classification :

• Logistic Regression
• K- Nearest Neighbors (K-NN)
• Support Vector Machine
• Kernel SVM
• Decision Tree Classification
• Random Forest Classification
• Naive Bayes

Clustering :

• K- Means Clustering
• Hierarchical Clustering

Association Rule Learning :

• Apriori
• Eclat

Dimension Reduction Techniques :

• Principal Component Analysis
• Linear Discriminant Analysis
• Kernel Principal Component Analysis

Deep Learning :

• Neural Network
• Convolutional Neural Network

Others

• Upper Confidence Bound
• Thompson Sampling
• Natural Language Processing
• K fold Cross Validation
• Grid Search
• XGBoost