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Getting Started with TensorFlow for Deep Learning

$125 | Duration: 2h 45m | Video: h264, 1920x1080 | Audio: AAC, 48kHz, 2 Ch | 885 MB
Genre: eLearning | Language: English | November 30, 2018

Apply Deep Learning to different data types and solve real-world problems with TensorFlow

We will not only get you up-and-running with deep learning, but also equip you with the skills to implement your own neural networks and apply them to the real world.

We will use TensorFlow, an efficient Python library used to create and train our neural networks. You'll learn the skills to implement their architecture quickly and efficiently without having to deal with minutiae.

You can rely on our expert guidance while learning the basic theory, backed up with relevant examples. We provide examples of neural networks, which you can use to highlight the key features. We then build up to more advanced networks. You'll learn to utilize a Convolutional Neural Network to classify images of handwritten text and then take your CNN further to perform object detection and localization in an image.

This course will quickly get you past the fundamentals of TensorFlow; you'll go on to more exciting things such as implementing a variety of image recognition tasks. All the code and this course's supporting files are available on GitHub at - https://github.com/PacktPublishing/Getting-Started-with-TensorFlow-for-Deep-Learning-

Style and Approach
This course will breeze through some essential textbook knowledge when it comes to machine learning. Following a brief math section, we get started with deep learning straight away.

Table of Contents
AN INTRODUCTION TO DEEP LEARNING AND TENSORFLOW
GETTING STARTED WITH TENSORFLOW
IMPLEMENTING YOUR FIRST NEURAL NETWORK
HANDWRITTEN DIGIT CLASSIFICATION
OBJECT DETECTION AND CLASSIFICATION

What You Will Learn
Properly understand the meaning of deep learning
Train a neural network and understand the often complicated process of backpropogation.
Create datasets in the correct format for use with TensorFlow—a key step when it comes to training your own models.
Create your own neural network architecture in TensorFlow using Keras, allowing you to define any architecture for your own needs.
Get accustomed to convolutional neural networks and understand why they are so powerful for image classification.
Use the TensorFlow ObjectDetection API to classify and localize objects in an image

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  1. TensorFlow深度学习入门 使用Tensorflow应用深度学习到不同的数据类型并解决真正的问题。我们不仅会带你开始学习深度学习,并且还会教给你部署你自己的神经网络并应用于真实工作中的技能。 我们将使用高效的Python类库Tensorflow,开发和训练我们的神经网络。你将学习快速高效地部署基础架构而无需纠结于细枝末节。你可以通过我们的专家教学学习基础理论,并通过相关例题实践。我们将给出你可以用于体验重要功能的神经外实例。然后我们将开发更高级的网络。你将学习利用卷积神经网络对手写文字图片分类,然后让你的CNN进一步执行图像中的对象识别和本地化。 主要内容:了解深度学习和Tensorflow;Tensorflow入门;部署你的第一个神经网络手写数字分类;对象识别和分类。
    wilde(特殊组-翻译)2周前 (12-04)