Concepts and Programming in PyTorch Magazine - First Edition 2018
Concepts and Programming in PyTorch Magazine - First Edition 2018
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In this issue
Concepts and Programming in PyTorch - First Edition 2018
Concepts and Programming in PyTorch Magazine Description:
Publisher: BPB Publications
Category: Academic
Language: English
Frequency: One Time
Learn to Demystify the neural networks with PyTorch
Key Features
● Basics concepts of PyTorch including CNN and RNN architecture are discussed in detailed manner.
● The worked out case studies are dealt in a detailed manner.
● Each chapter concludes with the observations of PyTorch to facilitate a better understanding of PyTorch.
● Abundant worked out coding examples.
● Highly self-explanatory and user-friendly approach.
Description
Book is written in a lucid manner to explain concepts in detail, with adequate emphasis on examples. To make clarity on the programming examples, logic is accurately explained and discussed through comments in the program itself. The topics covered in this book include starting the software through coding in software and writing programs.
The book features more on practical approach through ample examples covering simple to complex topics that address many core concepts and advanced topics.
What will you learn
● Linear Regression
● Convolution Neural Network (CNN)
● Recurrent Neural Network (RNN)
● PyTorch Datasets
Who this book is for
● Graduate Students- Computer Science/ CSE / IT/ Computer Applications
● Master Class Students—Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S.
● Researcher’s—Ph.D Research Scholars
Table of Contents
1. Introduction to PyTorch
2. Linear Regression
3. Convolution Neural Network (CNN)
4. Recurrent Neural Network (RNN)
5. PyTorch Datasets
6. Observation in PyTorch
About the Author
Chitra Vasudevan is a Technical director of the software company who had wide experience in Maths and Computer Science for more than 25+ years. Basically she is a Mainframe Specialist with the Knowledge of DB2, VSAM, IDMS, IMS Databases. She worked in the client server Architecture too with PowerBuilder, JAVA, VB, VC++. Apart from this she is an ISO 9000 certified Auditor and also a CMM Process oriented person. She had developed a lot of tools and apps in the field of Computer Science.
She had passed her M.Sc, M.Phil degree in Mathematics and is a Gold Medalist in Mathematics too. Later she entered in the field of Computer science and she worked as M.S. BITS Pilani Mentor for Software Engineering and Computer Design technology. Learn to Demystify the neural networks with PyTorch
Key Features
● Basics concepts of PyTorch including CNN and RNN architecture are discussed in detailed manner.
● The worked out case studies are dealt in a detailed manner.
● Each chapter concludes with the observations of PyTorch to facilitate a better understanding of PyTorch.
● Abundant worked out coding examples.
● Highly self-explanatory and user-friendly approach.
Description
Book is written in a lucid manner to explain concepts in detail, with adequate emphasis on examples. To make clarity on the programming examples, logic is accurately explained and discussed through comments in the program itself. The topics covered in this book include starting the software through coding in software and writing programs.
The book features more on practical approach through ample examples covering simple to complex topics that address many core concepts and advanced topics.
What will you learn
● Linear Regression
● Convolution Neural Network (CNN)
● Recurrent Neural Network (RNN)
● PyTorch Datasets
Who this book is for
● Graduate Students- Computer Science/ CSE / IT/ Computer Applications
● Master Class Students—Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S.
● Researcher’s—Ph.D Research Scholars
Table of Contents
1. Introduction to PyTorch
2. Linear Regression
3. Convolution Neural Network (CNN)
4. Recurrent Neural Network (RNN)
5. PyTorch Datasets
6. Observation in PyTorch
About the Author
Chitra Vasudevan is a Technical director of the software company who had wide experience in Maths and Computer Science for more than 25+ years. Basically she is a Mainframe Specialist with the Knowledge of DB2, VSAM, IDMS, IMS Databases. She worked in the client server Architecture too with PowerBuilder, JAVA, VB, VC++. Apart from this she is an ISO 9000 certified Auditor and also a CMM Process oriented person. She had developed a lot of tools and apps in the field of Computer Science.
She had passed her M.Sc, M.Phil degree in Mathematics and is a Gold Medalist in Mathematics too. Later she entered in the field of Computer science and she worked as M.S. BITS Pilani Mentor for Software Engineering and Computer Design technology. Learn to Demystify the neural networks with PyTorch
Key Features
● Basics concepts of PyTorch including CNN and RNN architecture are discussed in detailed manner.
● The worked out case studies are dealt in a detailed manner.
● Each chapter concludes with the observations of PyTorch to facilitate a better understanding of PyTorch.
● Abundant worked out coding examples.
● Highly self-explanatory and user-friendly approach.
Description
Book is written in a lucid manner to explain concepts in detail, with adequate emphasis on examples. To make clarity on the programming examples, logic is accurately explained and discussed through comments in the program itself. The topics covered in this book include starting the software through coding in software and writing programs.
The book features more on practical approach through ample examples covering simple to complex topics that address many core concepts and advanced topics.
What will you learn
● Linear Regression
● Convolution Neural Network (CNN)
● Recurrent Neural Network (RNN)
● PyTorch Datasets
Who this book is for
● Graduate Students- Computer Science/ CSE / IT/ Computer Applications
● Master Class Students—Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S.
● Researcher’s—Ph.D Research Scholars
Table of Contents
1. Introduction to PyTorch
2. Linear Regression
3. Convolution Neural Network (CNN)
4. Recurrent Neural Network (RNN)
5. PyTorch Datasets
6. Observation in PyTorch
About the Author
Chitra Vasudevan is a Technical director of the software company who had wide experience in Maths and Computer Science for more than 25+ years. Basically she is a Mainframe Specialist with the Knowledge of DB2, VSAM, IDMS, IMS Databases. She worked in the client server Architecture too with PowerBuilder, JAVA, VB, VC++. Apart from this she is an ISO 9000 certified Auditor and also a CMM Process oriented person. She had developed a lot of tools and apps in the field of Computer Science.
She had passed her M.Sc, M.Phil degree in Mathematics and is a Gold Medalist in Mathematics too. Later she entered in the field of Computer science and she worked as M.S. BITS Pilani Mentor for Software Engineering and Computer Design technology. Learn to Demystify the neural networks with PyTorch
Key Features
● Basics concepts of PyTorch including CNN and RNN architecture are discussed in detailed manner.
● The worked out case studies are dealt in a detailed manner.
● Each chapter concludes with the observations of PyTorch to facilitate a better understanding of PyTorch.
● Abundant worked out coding examples.
● Highly self-explanatory and user-friendly approach.
Description
Book is written in a lucid manner to explain concepts in detail, with adequate emphasis on examples. To make clarity on the programming examples, logic is accurately explained and discussed through comments in the program itself. The topics covered in this book include starting the software through coding in software and writing programs.
The book features more on practical approach through ample examples covering simple to complex topics that address many core concepts and advanced topics.
What will you learn
● Linear Regression
● Convolution Neural Network (CNN)
● Recurrent Neural Network (RNN)
● PyTorch Datasets
Who this book is for
● Graduate Students- Computer Science/ CSE / IT/ Computer Applications
● Master Class Students—Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S.
● Researcher’s—Ph.D Research Scholars
Table of Contents
1. Introduction to PyTorch
2. Linear Regression
3. Convolution Neural Network (CNN)
4. Recurrent Neural Network (RNN)
5. PyTorch Datasets
6. Observation in PyTorch
About the Author
Chitra Vasudevan is a Technical director of the software company who had wide experience in Maths and Computer Science for more than 25+ years. Basically she is a Mainframe Specialist with the Knowledge of DB2, VSAM, IDMS, IMS Databases. She worked in the client server Architecture too with PowerBuilder, JAVA, VB, VC++. Apart from this she is an ISO 9000 certified Auditor and also a CMM Process oriented person. She had developed a lot of tools and apps in the field of Computer Science.
She had passed her M.Sc, M.Phil degree in Mathematics and is a Gold Medalist in Mathematics too. Later she entered in the field of Computer science and she worked as M.S. BITS Pilani Mentor for Software Engineering and Computer Design technology. Learn to Demystify the neural networks with PyTorch
Key Features
● Basics concepts of PyTorch including CNN and RNN architecture are discussed in detailed manner.
● The worked out case studies are dealt in a detailed manner.
● Each chapter concludes with the observations of PyTorch to facilitate a better understanding of PyTorch.
● Abundant worked out coding examples.
● Highly self-explanatory and user-friendly approach.
Description
Book is written in a lucid manner to explain concepts in detail, with adequate emphasis on examples. To make clarity on the programming examples, logic is accurately explained and discussed through comments in the program itself. The topics covered in this book include starting the software through coding in software and writing programs.
The book features more on practical approach through ample examples covering simple to complex topics that address many core concepts and advanced topics.
What will you learn
● Linear Regression
● Convolution Neural Network (CNN)
● Recurrent Neural Network (RNN)
● PyTorch Datasets
Who this book is for
● Graduate Students- Computer Science/ CSE / IT/ Computer Applications
● Master Class Students—Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S.
● Researcher’s—Ph.D Research Scholars
Table of Contents
1. Introduction to PyTorch
2. Linear Regression
3. Convolution Neural Network (CNN)
4. Recurrent Neural Network (RNN)
5. PyTorch Datasets
6. Observation in PyTorch
About the Author
Chitra Vasudevan is a Technical director of the software company who had wide experience in Maths and Computer Science for more than 25+ years. Basically she is a Mainframe Specialist with the Knowledge of DB2, VSAM, IDMS, IMS Databases. She worked in the client server Architecture too with PowerBuilder, JAVA, VB, VC++. Apart from this she is an ISO 9000 certified Auditor and also a CMM Process oriented person. She had developed a lot of tools and apps in the field of Computer Science.
She had passed her M.Sc, M.Phil degree in Mathematics and is a Gold Medalist in Mathematics too. Later she entered in the field of Computer science and she worked as M.S. BITS Pilani Mentor for Software Engineering and Computer Design technology. Learn to Demystify the neural networks with PyTorch
Key Features
● Basics concepts of PyTorch including CNN and RNN architecture are discussed in detailed manner.
● The worked out case studies are dealt in a detailed manner.
● Each chapter concludes with the observations of PyTorch to facilitate a better understanding of PyTorch.
● Abundant worked out coding examples.
● Highly self-explanatory and user-friendly approach.
Description
Book is written in a lucid manner to explain concepts in detail, with adequate emphasis on examples. To make clarity on the programming examples, logic is accurately explained and discussed through comments in the program itself. The topics covered in this book include starting the software through coding in software and writing programs.
The book features more on practical approach through ample examples covering simple to complex topics that address many core concepts and advanced topics.
What will you learn
● Linear Regression
● Convolution Neural Network (CNN)
● Recurrent Neural Network (RNN)
● PyTorch Datasets
Who this book is for
● Graduate Students- Computer Science/ CSE / IT/ Computer Applications
● Master Class Students—Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S.
● Researcher’s—Ph.D Research Scholars
Table of Contents
1. Introduction to PyTorch
2. Linear Regression
3. Convolution Neural Network (CNN)
4. Recurrent Neural Network (RNN)
5. PyTorch Datasets
6. Observation in PyTorch
About the Author
Chitra Vasudevan is a Technical director of the software company who had wide experience in Maths and Computer Science for more than 25+ years. Basically she is a Mainframe Specialist with the Knowledge of DB2, VSAM, IDMS, IMS Databases. She worked in the client server Architecture too with PowerBuilder, JAVA, VB, VC++. Apart from this she is an ISO 9000 certified Auditor and also a CMM Process oriented person. She had developed a lot of tools and apps in the field of Computer Science.
She had passed her M.Sc, M.Phil degree in Mathematics and is a Gold Medalist in Mathematics too. Later she entered in the field of Computer science and she worked as M.S. BITS Pilani Mentor for Software Engineering and Computer Design technology.
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