Machine Learning Journey
A comprehensive showcase of my learning path through supervised learning, neural networks, unsupervised learning, and reinforcement learning algorithms.
3 Comprehensive Courses
From regression and classification to advanced neural networks and reinforcement learning
Practical Implementations
Hands-on code examples and projects built using Python, NumPy, TensorFlow, and scikit-learn
Interactive Demos
See machine learning algorithms in action with demonstrations like the Lunar Lander
Core ML Concepts
Deep understanding of fundamental algorithms and advanced techniques in machine learning
About This Specialization
The Machine Learning Specialization is a comprehensive program developed by Andrew Ng, covering the theoretical foundations and practical applications of machine learning algorithms. This showcase presents my journey through all three courses, featuring completed assignments, code implementations, and projects.
Throughout this specialization, I gained hands-on experience implementing various machine learning algorithms from scratch, starting with basic regression models and advancing to complex neural networks and reinforcement learning agents.
Skills Acquired
Course Structure
Supervised Machine Learning
Regression and classification algorithms, including linear regression, logistic regression, and gradient descent.
Advanced Learning Algorithms
Neural networks, decision trees, and practical machine learning advice on bias, variance, and error analysis.
Unsupervised & RL
Clustering, anomaly detection, recommender systems, and reinforcement learning techniques.