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)

Book Description

Topics included: 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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