Applied deep learning
design and implement your own neural networks to solve real world problems
Bibliographic details
Additional authors
Kumar, Neeraj
Summary
Applied Deep Learning: Design and Implement Your Own Neural Networks to Solve Real-World Problems provides a practical introduction to artificial intelligence, machine learning, and deep learning using Python. It explains neural-network fundamentals and progresses to convolutional neural networks, object detection and localization using YOLO, recurrent neural networks (RNNs), GRUs, LSTMs, Siamese networks, and generative adversarial networks (GANs). The book focuses on applying these techniques to real-world problems such as image recognition, sequence learning, object detection, and image generation.