TensorFlow 机器学习 Cookbook Application icon

TensorFlow 机器学习 Cookbook 2.0

10.6 MB / 10+ Downloads / Rating 5.0 - 1 reviews


See previous versions

TensorFlow 机器学习 Cookbook, developed and published by dafengstudio, has released its latest version, 2.0, on 2024-11-13. This app falls under the Books & Reference category on the Google Play Store and has achieved over 1000 installs. It currently holds an overall rating of 5.0, based on 1 reviews.

TensorFlow 机器学习 Cookbook APK available on this page is compatible with all Android devices that meet the required specifications (Android 4.1+). It can also be installed on PC and Mac using an Android emulator such as Bluestacks, LDPlayer, and others.

Read More

App Screenshot

App Screenshot

App Details

Package name: com.dafengstudio.tensorflowcookbook

Updated: 3 months ago

Developer Name: dafengstudio

Category: Books & Reference

New features: Show more

App Permissions: Show more

Installation Instructions

This article outlines two straightforward methods for installing TensorFlow 机器学习 Cookbook on PC Windows and Mac.

Using BlueStacks

  1. Download the APK/XAPK file from this page.
  2. Install BlueStacks by visiting http://bluestacks.com.
  3. Open the APK/XAPK file by double-clicking it. This action will launch BlueStacks and begin the application's installation. If the APK file does not automatically open with BlueStacks, right-click on it and select 'Open with...', then navigate to BlueStacks. Alternatively, you can drag-and-drop the APK file onto the BlueStacks home screen.
  4. Wait a few seconds for the installation to complete. Once done, the installed app will appear on the BlueStacks home screen. Click its icon to start using the application.

Using LDPlayer

  1. Download and install LDPlayer from https://www.ldplayer.net.
  2. Drag the APK/XAPK file directly into LDPlayer.

If you have any questions, please don't hesitate to contact us.

Previous Versions

TensorFlow 机器学习 Cookbook 2.0
2024-11-13 / 10.6 MB / Android 4.1+

About this app

tensorflow 0.1.0 文档
0:TensorFlow 机器学习 Cookbook (version : 0.1.0)
1:TensorFlow如何工作
15:变量和张量的声明
30:使用占位符和变量
38:矩阵
54:操作符的声明
62:载入激活函数
72:数据资源
83:资源库
89:本章学习模块
100:计算图
101:分层嵌套操作
102:多层操作
103:载入损失函数
104:载入反向传播
105:随机和批量训练
106:结合训练
107:模型评估
108:本章学习模块
111:矩阵转置
112:矩阵分解法
113:TensorFLow的线性回归
114:线性回归的损失函数
115:Deming回归(全回归)
116:套索(Lasso)回归和岭(Ridge)回归
117:弹性网(Elastic Net)回归
118:逻辑(Logistic)回归
119:本章学习模块
122:引言
123:线性支持向量机
124:回归线性回归
125:TensorFlow中的核
126:非线性支持向量机
127:多类支持向量机
128:本章学习模块
131:引言
132:最近邻法的使用
133:文本距离函数
134:计算混合距离函数
135:地址匹配
136:图像处理的近邻法
137:本章学习模块
140:引言
141:载入操作门
142:门运算和激活函数
143:载入一层神经网络
144:载入多层神经网络
145:使用多层神经网络
146:线性模型预测改善
147:神经网络学习井字棋
148:本章学习模块
151:引言
152:词袋 (Bag of Words)
153:词频-逆文本频率 (TF-IDF)
154:运用Skip-Gram
155:CBOW (Continuous Bag fo Words)
156:Word2Vec应用实例
157:Doc2Vec情感分析 (Sentiment Analysis)
158:神经网络学习井字棋
159:本章学习模块
162:引言
163:简单卷积神经网络 (Simple CNNs)
164:高级卷积神经网络 (Advanced CNNs)
165:重新训练一个存在架构
166:使用Stylenet/Neural-Style
167:运用Deep Dream
168:引言
169:卷积神经网络模型用于垃圾信息检测
170:LSTM模型用于文本生成
171:堆叠多层LSTM
172:创建段对段模型翻译 (Seq2Seq)
173:训练Siamese相似度测量
174:单元测试
175:使用多个执行器 (设备)
176:TensorFlow平行化
177:TensorFlow开发贴士
178:TensorFlow开发实例
179:计算图可视化(用Tensorboard)
180:遗传算法
181:K-means聚类分析
182:解决体系常微分方程
183:随机森林
184:TensorFlow中的Keras

New features

TensorFlow 机器学习 Cookbook

App Permissions

Allows an application to read from external storage.
Allows an application to write to external storage.
Allows applications to open network sockets.
Allows applications to access information about networks.
Allows using PowerManager WakeLocks to keep processor from sleeping or screen from dimming.