/Machine-Learning

Machine learning basics

Primary LanguageJupyter Notebook

Machine Learning

Machine Learning Algorithms and models in Python

TOPICS:-

  1. Data Preprocessing

2 Regression -simple linear -Multiple linear -Polynomial -Support Vector -Decision Tree -Random Forest

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

4.Clustering - K-Means Clustering - Hierarchical Clustering

5.Association Rule Learning Models - Apriori - Eclat

6.Reinforcement Learning

7.Natural Language Processing

8.Deep Learning

-ANN
-CNN

9.Dimensionality Reduction techniques

10.Model Selection and XGBoost