Everything related to this project started from the following paper: Speed/accuracy trade-offs for modern convolutional object detectors(https://arxiv.org/abs/1611.10012) by Huang J, Rathod V, Sun C, Zhu M, Korattikara A, Fathi A, Fischer I, Wojna Z, Song Y, Guadarrama S, Murphy K, CVPR 2017. Concluding this chapter, we have to thank all the contributors of the TensorFlow object detection API for their great job programming the API and making it open-source and thus free and accessible to anyone: Jonathan Huang, Vivek Rathod, Derek Chow, Chen Sun, Menglong Zhu, Matthew Tang, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang Song, Sergio Guadarrama, Jasper Uijlings, Viacheslav Kovalevskyi, Kevin Murphy. We also cannot forget to thank Dat Tran for his inspirational posts on medium of two MIT licensed projects on how to use the TensorFlow object...
TensorFlow Deep Learning Projects
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TensorFlow Deep Learning Projects
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Overview of this book
TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects.
TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. You'll learn how to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing this, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation and use reinforcement learning techniques to play games.
By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.
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Current Title:
TensorFlow Deep Learning Projects
Table of Contents (12 chapters)
Preface
Free Chapter
Recognizing traffic signs using Convnets
Annotating Images with Object Detection API
Caption Generation for Images
Building GANs for Conditional Image Creation
Stock Price Prediction with LSTM
Create and Train Machine Translation Systems
Train and Set up a Chatbot, Able to Discuss Like a Human
Detecting Duplicate Quora Questions
Building a TensorFlow Recommender System
Video Games by Reinforcement Learning
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