ishwarvenugopal / ML-DL_Implementation

Examples for various ML implementations in Python

Example codes for implementing different techniques in Machine Learning, Deep Learning and Data Science

Note: The codes are combined from various sources across the internet

The following techniques have been implemented:

Machine Learning Models:

• Decision Tree Classifier
• K-nn classifier
• Support Vector Machine
• Random Forest Classifier
• Naive Bayes Classifier
• Linear Regression
• Logistic Regression
• DBSCAN Clustering
• K-Means Clustering

Data Analysis

• Data Analysis with Pandas
• PCA (Dimensionality Reduction)
• Outlier Detection
• Feature Selection
• Bootstrapping
• Permutation Test (p-value)

Deep Learning

• Convolutional Neural Networks (Image Classification using MNIST and CIFAR-10 dataset)
• Multi-layer Perceptron (Using PyTorch and Keras framework)