IIIT Hyderabad – Certification Program | Hands-On Machine Learning & Deep Learning
Welcome to my repository of lab notebooks and projects completed as part of the Applied AI/ML Training Program by IIIT Hyderabad. This collection reflects my practical learning journey through core machine learning, neural networks, data processing, and algorithmic thinking — built from the ground up using Python and modern ML libraries.
- Core ML Algorithms implemented from scratch
- Clean visualizations & intuitive explanations
- Real-world data preprocessing and model tuning
- Neural Network implementation using TensorFlow/Keras
- Modular, reproducible, and Colab-compatible notebooks
| Module | Focus Areas |
|---|---|
| Module 1 | Data Transformation, Encoding, Feature Scaling |
| Module 2 | PCA, Manifold Learning, t-SNE |
| Module 3 | Distance Metrics, KNN from scratch, Text Classification |
| Module 4 | Gradient Descent, Perceptron, Linear Regression |
| Module 5 | Clustering, Probability Theory |
| Module 6 | Neural Networks, Activation Functions, Feedforward Design |
| Add-ons | Speech Processing, Linear Algebra Review, NN Tutorials |
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Language: Python
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Environment: Google Colab / Jupyter Notebook
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Libraries:
- Data:
NumPy,Pandas,Matplotlib,Seaborn - ML:
scikit-learn,TensorFlow,Keras
- Data:
- Build strong foundations in machine learning and AI
- Apply concepts through code, rather than just theory
- Develop confidence in creating models from scratch
- Tackle real datasets and uncover insights through exploration
This repository is part of the 6-month Applied AI & Machine Learning Certification Program by IIIT-Hyderabad, focused on hands-on implementation, algorithmic thinking, and problem-solving with code.
Feel free to explore, run the notebooks, and build upon them!