Hands-On Convolutional Neural Networks with TensorFlow
Solve Computer Vision Problems with Modeling in TensorFlow and Python
|Price||$29.99 - $45.13
|Authors||Iffat Zafar, Giounona Tzanidou, Richard Burton, Nimesh Patel, Leonardo Araujo|
|Format||Paper book / ebook (PDF)|
Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time!
We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation.
After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks.
Later on, you will see useful tips on machine learning best practices and troubleshooting. Finally, you will learn how to apply your models on large datasets of millions of images.
by Giancarlo Zaccone, Md. Rezaul Karim
Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks.This book is conce...
Price: $31.99 | Publisher: Packt Publishing | Release: 2018
by Dipanjan Sarkar, Raghav Bali, Tamoghna Ghosh
Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems.The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts...
Price: $44.99 | Publisher: Packt Publishing | Release: 2018
by Will Ballard
TensorFlow is Google's popular offering for machine learning and deep learning, quickly becoming a favorite tool for performing fast, efficient, and accurate deep learning tasks.Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations of real-world projects, teaching you how to leverage TensorFlow's capabi...
Price: $24.99 | Publisher: Packt Publishing | Release: 2018
by Navin Kumar Manaswi
Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Appli...
Price: $39.99 | Publisher: Apress | Release: 2018
by Aurelien Geron
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, a...
Price: $29.49 | Publisher: O'Reilly Media | Release: 2017
by Rajdeep Dua, Manpreet Singh Ghotra
Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy.The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popul...
Price: $34.99 | Publisher: Packt Publishing | Release: 2018
by Simeon Kostadinov
Developers struggle to find an easy-to-follow learning resource for implementing Recurrent Neural Network (RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve results. This book will teach yo...
Price: $29.99 | Publisher: Packt Publishing | Release: 2018
by Palash Goyal, Sumit Pandey, Karan Jain
Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models.You'll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with...
Price: $30.01 | Publisher: Apress | Release: 2018