 |
ISBN
| 9781788474221 | |
DDC
| 006.31 | |
Tác giả CN
| Sherif, Ahmed | |
Nhan đề
| Apache Spark deep learning cookbook : over 80 recipes that streamline deep learning in a distributed environment with apache spark / Ahmed Sherif, Amrith Ravindra | |
Thông tin xuất bản
| Birmingham, UK : Packt Publishing, 2018 | |
Mô tả vật lý
| 462 pages. : illustrations ; 24 cm. | |
Phụ chú
| Includes index | |
Tóm tắt
| With the help of the Apache Spark Deep Learning Cookbook, you'll work through specific recipes to generate outcomes for deep learning algorithms, without getting bogged down in theory. From setting up Apache Spark for deep learning to implementing types of neural net, this book tackles both common and not so common problems to perform deep learning on a distributed environment. In addition to this, you'll get access to deep learning code within Spark that can be reused to answer similar problems or tweaked to answer slightly different problems. You will also learn how to stream and cluster your data with Spark. Once you have got to grips with the basics, you'll explore how to implement and deploy deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in Spark, using popular libraries such as TensorFlow and Keras | |
Từ khóa tự do
| Data mining | |
Từ khóa tự do
| Big data | |
Từ khóa tự do
| Information visualization | |
Từ khóa tự do
| Machine learning | |
Từ khóa tự do
| Electronic data processing--Distributed processing | |
Khoa
| Khoa Công nghệ Thông tin | |
Tác giả(bs) CN
| Ravindra, Amrith | |
Địa chỉ
| Thư Viện Đại học Nguyễn Tất Thành |
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| 245 | |aApache Spark deep learning cookbook : |bover 80 recipes that streamline deep learning in a distributed environment with apache spark / |cAhmed Sherif, Amrith Ravindra |
|---|
| 260 | |aBirmingham, UK : |bPackt Publishing, |c2018 |
|---|
| 300 | |a462 pages. : |billustrations ; |c24 cm. |
|---|
| 500 | |aIncludes index |
|---|
| 520 | |aWith the help of the Apache Spark Deep Learning Cookbook, you'll work through specific recipes to generate outcomes for deep learning algorithms, without getting bogged down in theory. From setting up Apache Spark for deep learning to implementing types of neural net, this book tackles both common and not so common problems to perform deep learning on a distributed environment. In addition to this, you'll get access to deep learning code within Spark that can be reused to answer similar problems or tweaked to answer slightly different problems. You will also learn how to stream and cluster your data with Spark. Once you have got to grips with the basics, you'll explore how to implement and deploy deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in Spark, using popular libraries such as TensorFlow and Keras |
|---|
| 541 | |aMua |
|---|
| 653 | |aData mining |
|---|
| 653 | |aBig data |
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| 653 | |aInformation visualization |
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| 653 | |aMachine learning |
|---|
| 653 | |aElectronic data processing--Distributed processing |
|---|
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| 700 | |aRavindra, Amrith |
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| 852 | |aThư Viện Đại học Nguyễn Tất Thành |
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