Reports of all assignment are available in ./Report directory
- Classification on FMNIST Dataset.
- Performed Analysis of Naive Bayes Classifier.
- Performed Analysis for Classification on MNIST dataset.
- Performed K-Fold cross validation with analysis.
- Plotted various evaluation graphs like ROC, DET, Confusion Metric.
- Performed Decorrelation on given dataset.
- Incorporated Risk Matrix for Naive Bayes classifier.
- Plotted Decision Boundary using mesh grid.
- Performed Classification with some missing data points value.
- Performed Classification on Yale Face Dataset and CIFAR-10 Dataset.
- Implemented PCA & LDA from scratch.
- Did analysis using 5-Fold Cross Validation
- Analysis for PCA with varying Eigen Energy.
- Ensemble Learning:
- Implemented Bagging from scratch using decision trees.
- Implemented Ada-Boosting from scratch using decision tree classifier.
- Performed Analysis with 5-Fold cross validation.
- Analysis of using different Normalization techniqies like Z-Score, MinMax Normalization and Tanh.
- Implemented generic layers Neural Network from scratch.
- Analysis with different Activation functions.
- Implemented Auto Encoder using PyTorch on MNIST Dataset. Trained a neural network using the reduced dimension from Auto Encoder.
- Hands on with Panda Library.
- Did Feature Selection, Extraction and Feature Clustering for labeled data and unlabeled data.
- Private Kaggle Competition of Image Classification.
- Data included 20 classes and 10K Train Samples with 1K Test samples.