Machine-Learning-Engineering-Portfolio

This repository contains implementations of machine learning algorithms, techniques, and end-to-end projects across the ML pipeline.

Machine Learning & Deep Learning

Supervised Learning: Linear Regression, Logistic Regression, LASSO, Random Forests, Gradient Boosting, K-Nearest Neighbours
Unsupervised Learning: Clustering, K-Means, DBSCAN, PCA, Dimensionality Reduction
Ensemble Methods: Decision Trees(CART), Random Forest, Bagging, Gradient Boosting, Stacking, XGBoost
Deep Learning: Multilayer Perceptrons, Convolutional Neural Networks
Natural Language Processing: Sentiment Analysis, Text Classification

Each project directory contains:

Name		Name	Last commit message	Last commit date
Latest commit History 55 Commits
Boosting		Boosting
Classification and Regression Trees		Classification and Regression Trees
Climate Analysis		Climate Analysis
Clustering NYC Geographic Data		Clustering NYC Geographic Data
Convolutional Neural Networks (CNNs)		Convolutional Neural Networks (CNNs)
Decision Trees and Ensemble Methods for Predicting Knowledge Gain		Decision Trees and Ensemble Methods for Predicting Knowledge Gain
Density-Based Spatial Clustering of Applications with Noise		Density-Based Spatial Clustering of Applications with Noise
Ensembles		Ensembles
Exploratory Data Analysis		Exploratory Data Analysis
K-Nearest Neighbors		K-Nearest Neighbors
KMeans		KMeans
LASSO Regression		LASSO Regression
Linear Regression		Linear Regression
Logistic Regression		Logistic Regression
Medical Insurance Cost Prediction		Medical Insurance Cost Prediction
Neural Networks (Multi-Layer Perceptron)		Neural Networks (Multi-Layer Perceptron)
Principal Component Analysis		Principal Component Analysis
Regression Trees		Regression Trees
Regularization & Polynomial Regression		Regularization & Polynomial Regression
Regularization		Regularization
Sentiment Analysis		Sentiment Analysis
.DS_Store		.DS_Store
.gitignore		.gitignore
README.md		README.md