50+ Machine Learning Projects with Tajamul Khan

A curated collection of self-developed, hands-on and real world driven Machine Learning examples designed for both beginners and experts. The repository covers both supervised and unsupervised learning techniques, implemented in clean, easy-to-follow Jupyter Notebooks. Each project blends theory with practical application, using real datasets to illustrate how machine learning works in practice. Whether you’re starting your ML journey or aiming to expand your portfolio, this repo provides original, ready-to-use examples that showcase both technical skills and problem-solving expertise.

What you’ll find inside:

• Supervised learning projects – e.g., classification, regression
• Unsupervised learning projects – e.g., clustering, dimensionality reduction
• Step-by-step Jupyter Notebook implementations for easy learning and experimentation
• Practical, real-world datasets to reinforce theoretical concepts
• Projects suitable for portfolio building and interview preparation