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| 001 | 000045942237 | |
| 005 | 20200110133049 | |
| 008 | 180523s2017 nyua b 001 0 eng d | |
| 010 | ▼a 2017944429 | |
| 020 | ▼a 9781484228449 | |
| 020 | ▼a 1484228448 | |
| 035 | ▼a (KERIS)REF000018553621 | |
| 040 | ▼a BTCTA ▼b eng ▼c BTCTA ▼e rda ▼d YDX ▼d BDX ▼d TOH ▼d OCLCO ▼d LTSCA ▼d OCLCF ▼d OUP ▼d DLC ▼d 211009 | |
| 050 | 0 0 | ▼a TA345.5.M42 ▼b .K55 2017 |
| 082 | 0 4 | ▼a 006.31 ▼2 23 |
| 084 | ▼a 006.31 ▼2 DDCK | |
| 090 | ▼a 006.31 ▼b K49m | |
| 100 | 1 | ▼a Kim, Phil. |
| 245 | 1 0 | ▼a MATLAB deep learning : ▼b with machine learning, neural networks and artificial intelligence / ▼c Phil Kim. |
| 260 | ▼a [New York, NY] : ▼b Apress, ▼c c2017. | |
| 300 | ▼a xvii, 151 p. : ▼b ill. ; ▼c 24 cm. | |
| 504 | ▼a Includes bibliographical references and index. | |
| 630 | 0 0 | ▼a MATLAB. |
| 650 | 0 | ▼a Machine learning. |
| 650 | 0 | ▼a Neural networks (Computer science). |
| 770 | 0 8 | ▼i Online version: ▼a Kim, Phil. ▼t MATLAB deep learning ▼z 9781484228456 ▼w (211009) 000046011651 |
| 945 | ▼a KLPA |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 006.31 K49m | 등록번호 121244668 (13회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book.
With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage.
What You'll Learn
- Use MATLAB for deep learning
- Discover neural networks and multi-layer neural networks
- Work with convolution and pooling layers
- Build a MNIST example with these layers
Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.
New feature
Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book.
With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage.
You will:
- Use MATLAB for deep learning
- Discover neural networks and multi-layer neural networks
- Work with convolution and pooling layers
- Build a MNIST example with these layers
정보제공 :
목차
1. Machine Learning 2. Neural Network 3. Training of Multi-Layer Neural Network 4. Neural Network and Classification 5. Deep Learning 6. Convolutional Neural Network.