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　本課程面向企事業(yè)項(xiàng)目實(shí)際需要,秉承二十一年積累的教學(xué)品質(zhì)，TensorFlow for Image Recognition培訓(xùn)課程-以項(xiàng)目實(shí)現(xiàn)為導(dǎo)向,老師將會(huì)與您分享設(shè)計(jì)的全流程以及工具的綜合使用經(jīng)驗(yàn)、技巧。線上/線下/上門皆可,TensorFlow for Image Recognition培訓(xùn)課程-專家,課程可定制,熱線:4008699035。

　曙海的課程培養(yǎng)了大批受企業(yè)歡迎的工程師。曙海的課程在業(yè)內(nèi)有著響亮的知名度。大批企業(yè)和曙海
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培訓(xùn)內(nèi)容:
1、Machine Learning and Recursive Neural Networks (RNN) basics

NN and RNN

Backprogation

Long short-term memory (LSTM)

2、TensorFlow Basics

Creation, Initializing, Saving, and Restoring TensorFlow variables

Feeding, Reading and Preloading TensorFlow Data

How to use TensorFlow infrastructure to train models at scale

Visualizing and Evaluating models with TensorBoard

3、TensorFlow Mechanics 101

Tutorial Files

Prepare the Data

Build the Graph

Train the Model

Evaluate the Model

4、Advanced Usage

Threading and Queues

Distributed TensorFlow

Writing Documentation and Sharing your Model

Customizing Data Readers

Using GPUs

Manipulating TensorFlow Model Files

5、TensorFlow Serving

Introduction

Basic Serving Tutorial

Advanced Serving Tutorial

Serving Inception Model Tutorial

6、Convolutional Neural Networks

Overview

Code Organization

CIFAR-10 Model

Launching and Training the Model

Evaluating a Model

Training a Model Using Multiple GPU Cards

7、Deep Learning for MNIST

Setup

Load MNIST Data

Start TensorFlow InteractiveSession

Build a Softmax Regression Model

Placeholders

Variables

Predicted Class and Cost Function

Train the Model

Evaluate the Model

Build a Multilayer Convolutional Network

Weight Initialization

Convolution and Pooling

First Convolutional Layer

Second Convolutional Layer

Densely Connected Layer

Readout Layer

Train and Evaluate the Model

8、Image Recognition

Inception-v3

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TensorFlow for Image Recognition培訓(xùn)課程-

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