🐍 Python Machine Learning

Machine Learning with Python & scikit-learn — from fundamentals to production

Topics Covered

Supervised Learning

• 📊 Linear & Logistic Regression
• 🌳 Decision Trees & Random Forests
• 🎯 SVM (Support Vector Machines)
• 🔢 K-Nearest Neighbors

Unsupervised Learning

• 📦 K-Means Clustering
• 📉 PCA (Principal Component Analysis)
• 🔗 Hierarchical Clustering
• 🎭 Anomaly Detection

Deep Learning

• 🧠 Neural Networks with TensorFlow
• 🖼️ CNNs for Computer Vision
• 📝 RNNs and Transformers for NLP
• 🔄 Transfer Learning

NLP & Text

• 📊 Sentiment Analysis
• 📝 Text Classification
• 🔍 Named Entity Recognition
• 💬 Chatbot Development

Tech Stack

Category	Tools
ML	scikit-learn, TensorFlow, PyTorch
Data	pandas, NumPy, matplotlib
NLP	NLTK, spaCy, transformers
Notebooks	Jupyter Notebook
AI APIs	OpenAI, Ollama, Groq

Project Structure

├── 01-fundamentals/          # Python ML basics
├── 02-supervised-learning/   # Classification & regression
├── 03-unsupervised-learning/ # Clustering & dimensionality
├── 04-deep-learning/         # Neural networks
├── 05-nlp/                   # Natural language processing
├── 06-computer-vision/       # Image classification
├── 07-production/            # ML deployment & MLOps
└── notebooks/                # Jupyter notebooks

Author

@redoh — Senior Full-Stack Engineer | Machine Learning & Data Science