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Deep Learning With Python: Develop Deep Learning Models on Theano and TensorFlow Using Keras By Jason brownlee PDF

Download Book : Deep Learning With Python: Develop Deep Learning Models on Theano and TensorFlow Using Keras By Jason brownlee PDF




Informations about the book:


Title: Deep Learning With Python: Develop Deep Learning Models on Theano and TensorFlow Using Keras

Author: Jason Brownlee 

Size4.7 MB

FormatPDF

Year2016

Pages255


Book Contents:


I Introduction
1 Welcome
II Background
2 Introduction to Theano
3 Introduction to TensorFlow
4 Introduction to Keras
5 Project: Develop Large Models on GPUs Cheaply In the Cloud
III Multilayer Perceptrons
6 Crash Course In Multilayer Perceptrons 
7 Develop Your First Neural Network With Keras
8 Evaluate The Performance of Deep Learning Models
9 Use Keras Models With Scikit-Learn For General Machine Learning
10 Project: Multiclass Classification Of Flower Species
11 Project: Binary Classification Of Sonar Returns
12 Project: Regression Of Boston House Prices
IV Advanced Multilayer Perceptrons and Keras
13 Save Your Models For Later With Serialization
14 Keep The Best Models During Training With Checkpointing
15 Understand Model Behavior During Training By Plotting History
16 Reduce Overfitting With Dropout Regularization
17 Lift Performance With Learning Rate Schedules
V Convolutional Neural Networks
18 Crash Course In Convolutional Neural Networks
19 Project: Handwritten Digit Recognition
20 Improve Model Performance With Image Augmentation
21 Project Object Recognition in Photographs
22 Project: Predict Sentiment From Movie Reviews
VI Recurrent Neural Networks
23 Crash Course In Recurrent Neural Networks
24 Time Series Prediction with Multilayer Perceptrons
25 Time Series Prediction with LSTM Recurrent Neural Networks
26 Project: Sequence Classification of Movie Reviews
27 Understanding Stateful LSTM Recurrent Neural Networks
28 Project: Text Generation With Alice in Wonderland
VII Conclusions
29 How Far You Have Come
30 Getting More Help


Description:


This book is your guide to deep learning in Python. You will discover the Keras Python library for deep learning and how to use it to develop and evaluate deep learning models. In this book you will discover the techniques, recipes and skills in deep learning that you can then bring to your own machine learning projects.
Deep learning does have a lot of fascinating math under the covers, but you do not need to know it to be able to pick it up as a tool and wield it on important projects and deliver real value. From the applied perspective, deep learning is quite a shallow field and a motivated developer can quickly pick it up and start making very real and impactful contributions. This is my goal for you and this book is your ticket to that outcome.


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