Book Content
chapters • 15h44m total length
1. Building Deep Learning Environment
2. Training Neural Network for Prediction using Regression
3. Word Vector representationusing Word2VEC (skip-gram) for word prediction
4. Build NLP pipeline for Open-Domain Question Answering
5. Sequence-to-sequence models for building chatbots
6. Generative Language modelling using Bi-LSTM for content creation
7. Building Speech Recognition with DeepSpeech2
8. Handwritten digits classification using ConvNets
9. Real-time Object Detection using OpenCV and TensorFlow
10. Building Face Recognition using OpenFace and Clustering
11. Automated Image Captioning with NeuralTalk model
12. Pose Estimation on 3D models using ConvNets
13. Image translation using GANs for style transfer
14. Develop anautonomous Agents with Deep Reinforcement Learning
15. Summary and Next Steps in Your Deep Learning Career
