| Description |
1 online resource (310 pages) |
|
text file |
| Contents |
Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Recognizing traffic signs using Convnets; The dataset; The CNN network; Image preprocessing; Train the model and make predictions; Follow-up questions; Summary; Chapter 2: Annotating Images with Object Detection API; The Microsoft common objects in context; The TensorFlow object detection API; Grasping the basics of R-CNN, R-FCN and SSD models; Presenting our project plan; Setting up an environment suitable for the project; Protobuf compilation; Windows installation; Unix installation. |
|
Provisioning of the project codeSome simple applications; Real-time webcam detection; Acknowledgements; Summary; Chapter 3: Caption Generation for Images; What is caption generation?; Exploring image captioning datasets; Downloading the dataset; Converting words into embeddings; Image captioning approaches; Conditional random field; Recurrent neural network on convolution neural network; Caption ranking; Dense captioning; RNN captioning; Multimodal captioning; Attention-based captioning; Implementing a caption generation model; Summary; Chapter 4: Building GANs for Conditional Image Creation. |
|
Introducing GANsThe key is in the adversarial approach; A cambrian explosion; DCGANs; Conditional GANs; The project; Dataset class; CGAN class; Putting CGAN to work on some examples; MNIST; Zalando MNIST; EMNIST; Reusing the trained CGANs; Resorting to Amazon Web Service; Acknowledgements; Summary; Chapter 5: Stock Price Prediction with LSTM; Input datasets -- cosine and stock price; Format the dataset; Using regression to predict the future prices of a stock; Long short-term memory -- LSTM 101; Stock price prediction with LSTM; Possible follow -- up questions; Summary. |
|
Chapter 6: Create and Train Machine Translation SystemsA walkthrough of the architecture; Preprocessing of the corpora; Training the machine translator; Test and translate; Home assignments; Summary; Chapter 7: Train and Set up a Chatbot, Able to Discuss Like a Human; Introduction to the project; The input corpus; Creating the training dataset; Training the chatbot; Chatbox API; Home assignments; Summary; Chapter 8: Detecting Duplicate Quora Questions; Presenting the dataset; Starting with basic feature engineering; Creating fuzzy features; Resorting to TF-IDF and SVD features. |
|
Mapping with Word2vec embeddingsTesting machine learning models; Building a TensorFlow model; Processing before deep neural networks; Deep neural networks building blocks; Designing the learning architecture; Summary; Chapter 9: Building a TensorFlow Recommender System; Recommender systems; Matrix factorization for recommender systems; Dataset preparation and baseline; Matrix factorization; Implicit feedback datasets; SGD-based matrix factorization; Bayesian personalized ranking; RNN for recommender systems; Data preparation and baseline; RNN recommender system in TensorFlow; Summary. |
| Note |
Chapter 10: Video Games by Reinforcement Learning. |
| Summary |
This book is your guide to master deep learning with TensorFlow, with the help of 10 real-world projects. You will train high-performance models in TensorFlow to generate captions for images automatically, predict stocks' performance, create intelligent chatbots, perform large-scale text classification, develop recommendation systems, and more. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Artificial intelligence.
|
|
Artificial intelligence. |
| Genre/Form |
Electronic books.
|
|
Electronic books.
|
| Added Author |
Shanmugamani, rajalingappaa.
|
|
Boschetti, Alberto.
|
|
Massaron, Luca.
|
|
Thakur, Abhishek.
|
| Other Form: |
Print version: Grigorev, Alexey. TensorFlow Deep Learning Projects : 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning. Birmingham : Packt Publishing, ©2018 |
| ISBN |
9781788398381 (electronic book) |
|
1788398386 (electronic book) |
|
1788398068 |
|
9781788398060 |
| Standard No. |
9781788398060 |
|
