Welcome to the official repository for Week 2 and Week 3 labs of the GIKI-SkyElectric AI Bootcamp-1 2024, conducted by Usama Arshad. This repository contains the lab materials and assignments for the specified weeks, covering essential topics in Machine Learning and Deep Neural Networks. The contents include lab notebooks, datasets, and additional resources for practical learning.
- Lab 6: Implementing Support Vector Machines (SVM), Decision Trees, and Evaluation Metrics.
- Lab 7: Implementing Unsupervised Learning Algorithms including K-Means Clustering and Hierarchical Clustering.
- Lab 8: Feature Engineering and Model Selection Techniques.
- Lab 9: Implementing Regression Models including Linear Regression and Polynomial Regression.
- Lab 10: Implementing Classification Models including Logistic Regression and K-Nearest Neighbors (KNN).
- Lab 11: Implementing Basic Neural Networks.
- Lab 12: Implementing Regularization Techniques and Model Evaluation.
- Lab 13: Exploring Deep Learning Frameworks - Implementing Convolutional Neural Networks (CNNs).
- Lab 14: Implementing Transfer Learning and Fine-Tuning Pre-trained Models.
- Lab 15: Basic GAN.