1. Deploying over AWS: Train, Dockerize and then deploy your model on AWS
2. MobileNet & Other Edge DNNs: Training a DNN for EDGE Deployment from scratch. Understanding MobileNets and ShuffleNets
3. Face Recognition Part 1: Face Detection and Detection Strategies
4. OpenCV Refresher and Face Recognition. Part 2: Implementing Object Tracking and Stabilization, OpenCV and DLIB, for face recognition and others
5. Human Pose Estimation: State of Art HPE and Human Localization
6. Super-Resolution/Neural-Style-Transfer: Leveraging Transfer learning for NST and "Dense" models
7. Segmentation and Usage in Medical Domain: U-NET, its relatives and usage in Medical Science
8. GANs: Generative Adversarial Network and Variants
9. Encoders: Auto Encoders and Variational AutoEncoders
10. Neural Work Embedding: The Embedding Layer
11. Sequence Models: RNNs and LSTMs
12. GRU, Attention Mechanism & Transformers: Attention is all you need!
13. Image Captioning: Image Captioning - Integrating CNN + LSTMs
14. Speech: Advanced Speech Processing (TTS/STT)
14. CapStone Project: Hallowed be thy name
The training of network is completed on Google Colaboratory and deployed on AWS.
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