| Project # | Network Type | Project |
|---|---|---|
| 1 | LSTM + W2C | Sentiment Analysis |
| 2 | Generative Adversarial Network | Generate Synthetic Images |
| 3 | LSTM Autoencoder | Detect Anomalies in Time Series |
| 4 | Siamese Network | MNIST Handwritten Digits |
| 5 | Autoencoders | Reducing Dimensions In Data |
| 6 | Convolutional Neural Networks | COVID-19 Detection Using X-Rays |
| 7 | SARIMAX + FB Prophet | COVID-19 Time Series |
| 8 | Random Forest Classifier | Imbalanced CC Fraud Detection |
| 9 | Ensemble ( VGG19 + Xception ) | Malaria Dataset Classification |
| 10 | NLP TF Hub Models | NLP Transfer Learning |
| 11 | Simple Probabilistic Model | HAR Dataset Weights & Outputs Uncertainty |
| 12 | Plain FC NN | From Scratch in TF 2.x |
| 13 | BERT (Pytorch) | Sentiment Analysis Twitter SMILE dataset |
| 14 | Autoencoder | Image Denoising |
| 15 | 2D Convolutional NN | Visualizing Filters of CNNs |
| 16 | ResNet152 Transfer Learning | CIFAR10 Dataset & 96% Accuracy on Test Set |