Book Content
chapters • 15h48m total length
1. Setting Up Spark for Deep Learning Development
2. Creating a Neural Network in Spark
3. Pain Points of Convolutional Neural Networks
4. Pain Points of Recurrent Neural Networks
5. Predicting Fire Department Calls with Spark ML
6. Using LSTMs in Generative Networks
7. Natural Language Processing with TF-IDF
8. Real Estate Value Prediction using XGBoost
9. Predicting Apple Stock Market Cost with LSTM
10. Face Recognition using Deep Convolutional Networks
11. Creating and Visualizing Word Vectors Using Word2Vec
12. Creating a Movie Recommendation Engine with Keras
13. Image Classification with TensorFlow on Spark
