Deep Learning Quick Reference

Deep Learning Quick Reference includes essential tips, tricks, and hacks to train a variety of deep learning models such as CNNs, RNNs, LSTMs, and more. Supplemented with essential mathematics and theory, every chapter provides best practices and safe choices for training and fine-tuning your models in Keras and Tensorflow. (Limited-time offer)

Table of Contents

• The Building Blocks of Deep Learning
• Using Deep Learning to Solve Regression Problems
• Monitoring Network Training Using TensorBoard
• Using Deep Learning to Solve Binary Classification Problems
• Using Keras to Solve Multiclass Classification Problems
• Hyperparameter Optimization
• Training a CNN from Scratch
• Transfer Learning with Pretrained CNNs
• Training an RNN from scratch
• Training LSTMs with Word Embeddings from Scratch
• Training Seq2Seq Models
• Using Deep Reinforcement Learning
• Generative Adversarial Networks

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