Book Content
chapters • 14h32m total length
1. Getting Started with Deep Learning
2. Cancer Type Prediction using Recurrent Type Networks
3. Image Classification using Convolutional Neural Networks
4. Sentiment Analysis using Word2Vec and LSTM Networks
5. Image Classification using Transfer Learning
6. Real-Time Object Detection Using YOLO, JavaCV, and DL4J
7. Stock Price Prediction Using the LSTM Network
8. Distributed Deep Learning – Video Classification Using Convolutional-LSTM Networks
9. Using Deep Reinforcement Learning for a GridWorld Game
10. Movie Recommendation System using Factorization Machines
11. Discussion, Current Trends, and Outlook
