Grigorev / Kulkarni / Shanmugamani TensorFlow Deep Learning Projects

10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning
1. Auflage 2024
ISBN: 978-1-78839-838-1
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 320 Seiten

Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenariosKey Features - [*]Build efficient deep learning pipelines using the popular Tensorflow framework
- [*]Train neural networks such as ConvNets, generative models, and LSTMs
- [*]Includes projects related to Computer Vision, stock prediction, chatbots and more
Book DescriptionTensorFlow 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.What you will learn - Set up the TensorFlow environment for deep learning
- Construct your own ConvNets for effective image processing
- Use LSTMs for image caption generation
- Forecast stock prediction accurately with an LSTM architecture
- Learn what semantic matching is by detecting duplicate Quora questions
- Set up an AWS instance with TensorFlow to train GANs
- Train and set up a chatbot to understand and interpret human input
- Build an AI capable of playing a video game by itself –and win it!
Who this book is forThis book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book.

Autoren/Hrsg.

Grigorev, Alexey

Kulkarni, Srinivas

Shanmugamani, Rajalingappaa

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung

Inhaltsverzeichnis

Table of Contents - 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 & Train Machine Translation Systems
- Train and set up a Chatbot, able to discuss like a human
- Detecting Duplicate Quora Questions
- Building a TensorFlow Recommender Systems

- Video Games by Reinforcement learning

Über Autor(innen)

Grigorev Alexey :

Alexey Grigorev is a skilled data scientist, machine learning engineer, and software developer with more than 8 years of professional experience. He started his career as a Java developer working at a number of large and small companies, but after a while he switched to data science. Right now, Alexey works as a data scientist at Simplaex, where, in his day-to-day job, he actively uses Java and Python for data cleaning, data analysis, and modeling. His areas of expertise are machine learning and text mining.Shanmugamani Rajalingappaa :

Rajalingappaa Shanmugamani is currently working as an Engineering Manager for a Deep learning team at Kairos. Previously, he worked as a Senior Machine Learning Developer at SAP, Singapore and worked at various startups in developing machine learning products. He has a Masters from Indian Institute of TechnologyMadras. He has published articles in peer-reviewed journals and conferences and submitted applications for several patents in the area of machine learning. In his spare time, he coaches programming and machine learning to school students and engineers.