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The the Deep Learning with Pytorch Workshop : Build Deep Neural Networks and Artificial Intelligence Applications with Pytorch [electronic resource]
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Saleh, Hyatt. |
| 서명/저자사항 | The the Deep Learning with Pytorch Workshop[electronic resource] :Build Deep Neural Networks and Artificial Intelligence Applications with Pytorch. |
| 발행사항 | Birmingham : Packt Publishing, Limited, 2020. |
| 형태사항 | 1 online resource (329 p.) |
| 소장본 주기 | Master record variable field(s) change: 050, 082, 650 |
| ISBN | 1838981845 9781838981846 |
| 일반주기 |
Description based upon print version of record.
Exercise 4.02: Calculating the Output Shape of a Set of Convolutional and Pooling Layers |
| 내용주기 | Cover -- FM -- Copyright -- Table of Contents -- Preface -- Chapter 1: Introduction to Deep Learning and PyTorch -- Introduction -- Why Deep Learning? -- Applications of Deep Learning -- Introduction to PyTorch -- GPUs in PyTorch -- What Are Tensors? -- Exercise 1.01: Creating Tensors of Different Ranks Using PyTorch -- Advantages of Using PyTorch -- Disadvantages of Using PyTorch -- Key Elements of PyTorch -- The PyTorch autograd Library -- The PyTorch nn Module -- Exercise 1.02: Defining a Single-Layer Architecture -- The PyTorch optim Package -- Exercise 1.03: Training a Neural Network Activity 1.01: Creating a Single-Layer Neural Network -- Summary -- Chapter 2: Building Blocks of Neural Networks -- Introduction -- Introduction to Neural Networks -- What Are Neural Networks? -- Exercise 2.01: Performing the Calculations of a Perceptron -- Multi-Layer Perceptron -- The Learning Process of a Neural Network -- Forward Propagation -- The Calculation of Loss Functions -- Backward Propagation -- Gradient Descent -- Advantages and Disadvantages -- Advantages -- Disadvantages -- Introduction to Artificial Neural Networks -- Introduction to Convolutional Neural Networks Introduction to Recurrent Neural Networks -- Data Preparation -- Dealing with Messy Data -- Exercise 2.02: Dealing with Messy Data -- Data Rescaling -- Exercise 2.03: Rescaling Data -- Splitting the Data -- Exercise 2.04: Splitting a Dataset -- Disadvantages of Failing to Prepare Your Data -- Activity 2.01: Performing Data Preparation -- Building a Deep Neural Network -- Exercise 2.05: Building a Deep Neural Network Using PyTorch -- Activity 2.02: Developing a Deep Learning Solution for a Regression Problem -- Summary -- Chapter 3: A Classification Problem Using DNN -- Introduction Problem Definition -- Deep Learning in Banking -- Exploring the Dataset -- Data Preparation -- Building the Model -- ANNs for Classification Tasks -- A Good Architecture -- PyTorch Custom Modules -- Exercise 3.01: Defining a Model's Architecture Using Custom Modules -- Defining the Loss Function and Training the Model -- Activity 3.01: Building an ANN -- Dealing with an Underfitted or Overfitted Model -- Error Analysis -- Exercise 3.02: Performing Error Analysis -- Activity 3.02: Improving a Model's Performance -- Deploying Your Model -- Saving and Loading Your Model PyTorch for Production in C++ -- Building an API -- Exercise 3.03: Creating a Web API -- Activity 3.03: Making Use of Your Model -- Summary -- Chapter 4: Convolutional Neural Networks -- Introduction -- Building a CNN -- Why Are CNNs Used for Image Processing? -- The Image as Input -- Applications of CNNs -- Classification -- Localization -- Detection -- Segmentation -- The Building Blocks of CNNs -- Convolutional Layers -- Exercise 4.01: Calculating the Output Shape of a Convolutional Layer -- Pooling Layers |
| 요약 | With this hands-on, self-paced guide, you'll explore crucial deep learning topics and discover the structure and syntax of PyTorch. Challenging activities and interactive exercises will keep you motivated and encourage you to build intelligent applications effectively. |
| 일반주제명 | Machine learning. Python (Computer program language) |
| 언어 | 영어 |
| 기타형태 저록 | Print version:Saleh, HyattThe the Deep Learning with Pytorch Workshop : Build Deep Neural Networks and Artificial Intelligence Applications with PytorchBirmingham : Packt Publishing, Limited,c2020 |
| 대출바로가기 | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2532423 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00018789 | 006.31 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |
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