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Neural Networks with Keras Cookbook
Thisbookwilltakeyoufromthebasicsofneuralnetworkstoadvancedimplementationsofarchitecturesusingarecipe-basedapproach.Wewilllearnabouthowneuralnetworksworkandtheimpactofvarioushyperparametersonanetwork'saccuracyalongwithleveragingneuralnetworksforstructuredandunstructureddata.Later,wewilllearnhowtoclassifyanddetectobjectsinimages.Wewillalsolearntousetransferlearningformultipleapplications,includingaself-drivingcarusingConvolutionalNeuralNetworks.WewillgenerateimageswhileleveragingGANsandalsobyperformingimageencoding.Additionally,wewillperformtextanalysisusingwordvectorbasedtechniques.Later,wewilluseRecurrentNeuralNetworksandLSTMtoimplementchatbotandMachineTranslationsystems.Finally,youwilllearnabouttranscribingimages,audio,andgeneratingcaptionsandalsouseDeepQ-learningtobuildanagentthatplaysSpaceInvadersgame.Bytheendofthisbook,youwillhavedevelopedtheskillstochooseandcustomizemultipleneuralnetworkarchitecturesforvariousdeeplearningproblemsyoumightencounter.
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- How to do it...
- Getting ready
- Deep Q-learning to play Space Invaders game
- How to do it...
品牌：中圖公司
上架時間：2021-07-02 12:23:30
出版社：Packt Publishing
本書數字版權由中圖公司提供，并由其授權上海閱文信息技術有限公司制作發行
- Leave a review - let other readers know what you think 更新時間：2021-07-02 12:47:30
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- How it works…
- How to do it…
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- Sections
- Conventions used
- Download the color images
- Download the example code files
- To get the most out of this book
- What this book covers
- Who this book is for
- Preface
- Packt is searching for authors like you
- About the reviewer
- About the author
- Contributors
- Packt.com
- Why subscribe?
- About Packt
- Dedication
- Neural Networks with Keras Cookbook
- Copyright and Credits
- Title Page
- coverpage
- coverpage
- Title Page
- Copyright and Credits
- Neural Networks with Keras Cookbook
- Dedication
- About Packt
- Why subscribe?
- Packt.com
- Contributors
- About the author
- About the reviewer
- Packt is searching for authors like you
- Preface
- Who this book is for
- What this book covers
- To get the most out of this book
- Download the example code files
- Download the color images
- Conventions used
- Sections
- Getting ready
- How to do it…
- How it works…
- There's more…
- See also
- Get in touch
- Reviews
- Building a Feedforward Neural Network
- Introduction
- Architecture of a simple neural network
- Training a neural network
- Applications of a neural network
- Feed-forward propagation from scratch in Python
- Getting ready
- How to do it...
- Building back-propagation from scratch in Python
- Getting ready
- How to do it...
- There's more...
- Building a neural network in Keras
- How to do it...
- Installing Keras
- Building our first model in Keras
- Building a Deep Feedforward Neural Network
- Training a vanilla neural network
- Getting ready
- How to do it...
- How it works...
- Scaling the input dataset
- Getting ready
- How to do it...
- How it works...
- There's more...
- Impact on training when the majority of inputs are greater than zero
- Getting ready
- How to do it...
- Impact of batch size on model accuracy
- Getting ready
- How to do it...
- How it works...
- Building a deep neural network to improve network accuracy
- Getting ready
- How to do it...
- Varying the learning rate to improve network accuracy
- Getting ready
- How to do it...
- Varying the loss optimizer to improve network accuracy
- Getting ready
- There's more...
- Understanding the scenario of overfitting
- Overcoming over-fitting using regularization
- How to do it
- Overcoming overfitting using dropout
- Speeding up the training process using batch normalization
- How to do it...
- Applications of Deep Feedforward Neural Networks
- Introduction
- Predicting credit default
- Getting ready
- How to do it...
- How it works...
- Assigning weights for classes
- Getting ready
- How to do it...
- Predicting house prices
- Getting ready
- How to do it...
- Defining the custom loss function
- Categorizing news articles into topics
- Getting ready
- How to do it...
- Classifying common audio
- How to do it...
- Stock price prediction
- Getting ready
- How to do it...
- Leveraging a functional API
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- Defining weights for rows
- How to do it...
- Building a Deep Convolutional Neural Network
- Introduction
- Inaccuracy of traditional neural networks when images are translated
- How to do it...
- Problems with traditional NN
- Building a CNN from scratch using Python
- Getting ready
- Understanding convolution
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- From convolution activation to pooling
- How do convolution and pooling help?
- How to do it...
- Validating the CNN output
- CNNs to improve accuracy in the case of image translation
- Getting ready
- How to do it...
- Gender classification using CNNs
- Getting ready
- How to do it...
- There's more...
- Data augmentation to improve network accuracy
- Getting ready
- How to do it...
- Model accuracy without data augmentation
- Model accuracy with data augmentation
- Transfer Learning
- Gender classification of the person in an image using CNNs
- Getting ready
- How to do it...
- Scenario 1 – big images
- Scenario 2 – smaller images
- Scenario 3 – aggressive pooling on big images
- Gender classification of the person in image using the VGG16 architecture-based model
- Getting ready
- How to do it...
- Visualizing the output of the intermediate layers of a neural network
- Getting ready
- How to do it...
- Gender classification of the person in image using the VGG19 architecture-based model
- Getting ready
- How to do it...
- Gender classification using the Inception v3 architecture-based model
- How to do it...
- Gender classification of the person in image using the ResNet 50 architecture-based model
- How to do it...
- Detecting the key points within image of a face
- Getting ready
- How to do it...
- Detecting and Localizing Objects in Images
- Introduction
- Creating the dataset for a bounding box
- How to do it...
- Windows
- Ubuntu
- MacOS
- Generating region proposals within an image using selective search
- Getting ready
- How to do it...
- Calculating an intersection over a union between two images
- How to do it...
- Detecting objects using region proposal-based CNN
- Getting ready
- How to do it...
- Performing non-max suppression
- Getting ready
- How to do it...
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- Getting ready
- How to do it...
- There's more...
- Image Analysis Applications in Self-Driving Cars
- Traffic sign identification
- Getting ready
- How to do it...
- Predicting the angle within which a car needs to be turned
- Getting ready
- How to do it...
- Instance segmentation using the U-net architecture
- Getting ready
- How to do it...
- Semantic segmentation of objects in an image
- Getting ready
- How to do it...
- Image Generation
- Introduction
- Generating images that can fool a neural network using adversarial attack
- Getting ready
- How to do it...
- DeepDream algorithm to generate images
- Getting ready
- How to do it...
- Neural style transfer between images
- Getting ready
- How to do it...
- Generating images of digits using Generative Adversarial Networks
- Getting ready
- How to do it...
- There's more...
- Generating images using a Deep Convolutional GAN
- How to do it...
- Face generation using a Deep Convolutional GAN
- Getting ready
- How to do it...
- Face transition from one to another
- Getting ready
- How to do it...
- Performing vector arithmetic on generated images
- Getting ready
- How to do it...
- There's more...
- Encoding Inputs
- Introduction
- Need for encoding
- Need for encoding in text analysis
- Need for encoding in image analysis
- Need for encoding in recommender systems
- Encoding an image
- Getting ready
- How to do it...
- Vanilla autoencoder
- Multilayer autoencoder
- Convolutional autoencoder
- Grouping similar images
- Encoding for recommender systems
- Getting ready
- How to do it...
- Text Analysis Using Word Vectors
- Introduction
- Building a word vector from scratch in Python
- Getting ready
- How to do it...
- Measuring the similarity between word vectors
- Building a word vector using the skip-gram and CBOW models
- Getting ready
- How to do it
- Performing vector arithmetic using pre-trained word vectors
- How to do it...
- Creating a document vector
- Getting ready
- How to do it...
- Building word vectors using fastText
- Getting ready
- How to do it...
- Building word vectors using GloVe
- Getting ready
- How to do it...
- Building sentiment classification using word vectors
- How to do it...
- There's more...
- Building a Recurrent Neural Network
- Introduction
- Intuition of RNN architecture
- Interpreting an RNN
- Why store memory?
- Building an RNN from scratch in Python
- Getting ready
- How to do it...
- Validating the output
- Implementing RNN for sentiment classification
- How to do it...
- There's more...
- Building a LSTM Network from scratch in Python
- Getting ready
- How to do it...
- Validating the output
- Implementing LSTM for sentiment classification
- How to do it...
- Implementing stacked LSTM for sentiment classification
- How to do it...
- There's more...
- Applications of a Many-to-One Architecture RNN
- Generating text
- Getting ready
- How to do it...
- Movie recommendations
- Getting ready
- How to do it...
- Taking user history into consideration
- Topic-modeling using embeddings
- Getting ready
- How to do it...
- There's more...
- Forecasting the value of a stock's price
- Getting ready
- How to do it...
- The last five days' stock prices only
- The pitfalls
- Assigning different weights to different time periods
- The last five days' stock prices plus news data
- There's more...
- Sequence-to-Sequence Learning
- Introduction
- Returning sequences of outputs from a network
- Building a chatbot
- Getting ready
- How to do it...
- Intent extraction
- Putting it all together
- Machine translation
- Getting ready
- How to do it...
- Preprocessing the data
- Traditional many to many architecture
- Many to hidden to many architecture
- Encoder decoder architecture for machine translation
- Getting ready
- How to do it...
- Encoder decoder architecture with attention for machine translation
- How to do it...
- End-to-End Learning
- Introduction
- Connectionist temporal classification (CTC)
- Decoding CTC
- Calculating the CTC loss value
- Handwritten-text recognition
- Getting ready
- How to do it...
- Image caption generation
- Getting ready
- How to do it...
- Generating captions using beam search
- Getting ready
- How to do it...
- Audio Analysis
- Classifying a song by genre
- Getting ready
- How to do it...
- Generating music using deep learning
- Getting ready
- How to do it...
- Transcribing audio into text
- Getting ready
- How to do it...
- There's more...
- Reinforcement Learning
- The optimal action to take in a simulated game with a non-negative reward
- Getting ready
- How to do it...
- The optimal action to take in a state in a simulated game
- Getting ready
- How to do it...
- There's more...
- Q-learning to maximize rewards when playing Frozen Lake
- Getting ready
- How to do it...
- Deep Q-learning to balance a cart pole
- Getting ready
- How to do it...
- Deep Q-learning to play Space Invaders game
- Getting ready
- How to do it...
- Other Books You May Enjoy
- Leave a review - let other readers know what you think 更新時間：2021-07-02 12:47:30
