September 2017 | English | True PDF | ISBN: N/A | 332 Page
You're interested in deep learning and computer vision...
...but you don't know how to get started. Let me help.
Whether this is the first time you've worked with machine learning and neural networks or you're already a seasoned deep learning practitioner, Deep Learning for Computer Vision with Python is engineered from the ground up to help you reach expert status.
Take a sneak peek at what's inside...
This book has one goal — to help developers, researchers, and students just like yourself become experts in deep learning for image recognition and classification.
Inside this book you'll find:
Super practical walkthroughs that present solutions to actual, real-world image classification problems, challenges, and competitions.
Hands-on tutorials (with lots of code) that not only show you the algorithms behind deep learning for computer vision but their implementations as well.
A no-nonsense teaching style that is guaranteed to cut through all the cruft and help you master deep learning for image understanding and visual recognition.
Just getting started with deep learning? Or already a pro?
No problem, I have you covered either way.
Are you just getting started in deep learning? Don't worry; you won't get bogged down by tons of theory and complex equations. We'll start off with the basics of machine learning and neural networks. Learn in a fun, practical way with lots of code. You'll be a neural network ninja in no time, and be able to graduate to the more advanced content.
Are you already a seasoned deep learning pro? This book isn't just for beginners — there's advanced content in here, too. You'll discover how to train your own custom object detectors using deep learning. You'll build a custom framework that can be used to train very deep architectures on the challenging ImageNet dataset from scratch. I'll even show you my personal blueprint which I use to determine which deep learning techniques to apply when confronted with a new problem. Best of all, these solutions and tactics can be directly applied to your current job and research.
Regardless of your experience level, you'll find tremendous value inside Deep Learning for Computer Vision with Python, I guarantee it.
What is this book? And what does it to cover?
Deep Learning for Computer Vision with Python will make you an expert in deep learning for computer vision and visual recognition tasks.
Inside the book we will focus on:
Neural Networks and Machine Learning
Convolutional Neural Networks (CNNs)
Object detection/localization with deep learning
Training large-scale (ImageNet-level) networks
Hands on implementations using the Python programming language and the Keras (which is compatible with either TensorFlow or Theano) + mxnet libraries
After going through Deep Learning for Computer Vision with Python, you'll be able to solve real-world problems with deep learning.
You're probably wondering...
"Is this book right for me?"
This book is for developers, researchers, and students who have at least some programming experience and want to become proficient in deep learning for computer vision & visual recognition.
Maybe you:
Are a computer vision developer that utilizes OpenCV (among other image processing libraries) and are eager to level-up your skills.
Have experience with machine learning and want to break into neural networks/deep learning for image understanding.
Are a college student and want more than your university offers (or want to get ahead of your class).
Are a scientist looking to apply deep learning + computer vision algorithms to your research.
Utilize computer vision algorithms in your own projects but have yet to try deep learning.
Used deep learning in projects before, but never in the context of visual recognition and image understanding.
Write Python/machine learning code at your day job and are motivated to stand out from your coworkers.
Are a "machine learning hobbyist" who knows how to program and wants to understand what this "deep learning" thing is all about.
If any of these descriptions fit you, rest assured: you're the target student.
I wrote this book for you.
Utilize Python, Keras (with either a TensorFlow or Theano backend), and mxnet to build deep learning networks.
Python, Keras, and mxnet are all well-built tools that, when combined, create a powerful deep learning development environment that you can use to master deep learning for computer vision and visual recognition.
We'll be utilizing the Python programming language for all examples in this book. Python is an easy language to learn and is hands-down the best way to work with deep learning algorithms.
To build and train our deep learning networks we'll primarily be using the Keras library. Keras supports both TensorFlow and Theano, making it super easy to build and train networks quickly.
We'll also use mxnet, a deep learning library that specializes in distributed, multi-machine learning. The ability to parallelize training across GPUs/devices is critical when training deep neural network architectures on massive datasets (such as ImageNet).
More than just a book — this is your gateway to mastering deep learning.
Deep Learning for Computer Vision with Python is more than just a book. It's a complete package that is designed from the ground-up to help you master deep learning.
Each bundle includes:
发帖
雷达卡
加好友,备注cda
京公网安备 11010802022788号
论坛法律顾问：王进律师
知识产权保护声明
免责及隐私声明
提升卡
置顶卡
沉默卡
变色卡
抢沙发
千斤顶
显身卡
