MachineLearning-Portfolio

This is the collection of my machine learning applications and course project It contains the code for several projects and online course work

Including:

1. Data preprocessing templates
2. Regressoins
   • Linear, Polynomial
   • Support Vector
   • Decision Tree
   • Random Forest Regression
3. Classifications:
   • Logistic Regression
   • Support Vector Machine
   • Kernel SVM
   • Naive Bayes
   • Decision Tree
   • Random Forest
4. Clustering
   • K-Means
   • Hierarchical Clustering
5. Association Rule Learning
   • Apriori
   • Eclat
6. Reinforcement Learning
   • Upper Confidence Bound
   • Thompson Sampling
7. Natural Language Processing
8. Deep Learning
   • Artificial Neural Networks
   • Convolutional Neural Networks
9. Dimenstionality Reduction
   • Principle Component Analysis(PCA)
   • Linear Discriminant Analysis(LDA)
   • Kernal PCA
10. Model Slection
    • Grid Search
    • K-Fold Validation
    • XGBoost