Python Deep Learning Projects book will simplify and ease how deep learning works, and demonstrate how neural networks play a vital role in exploring predictive analytics across different domains. You will explore projects in the field of computational linguistics, computer vision, machine translation, pattern recognition and many more Insightful projects to master deep learning and neural network architectures using Python and Keras Key Features Explore deep learning across computer vision, natural language processing (NLP), and image processing Discover best practices for the training of deep neural networks and their deployment Access popular deep learning models as well as widely used neural network architectures Book DescriptionDeep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system. Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects. By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way What you will learn Set up a deep learning development environment on Amazon Web Services (AWS) Apply GPU-powered instances as well as the deep learning AMI Implement seq-to-seq networks for modeling natural language processing (NLP) Develop an end-to-end speech recognition system Build a system for pixel-wise semantic labeling of an image Create a system that generates images and their regions Who this book is forPython Deep Learning Projects is for you if you want to get insights into deep learning, data science, and artificial intelligence. This book is also for those who want to break into deep learning and develop their own AI projects. It is assumed that you have sound knowledge of Python programming
Python Deep Learning Projects book will simplify and ease how deep learning works, and demonstrate how neural networks play a vital role in exploring predictive analytics across different domains. You will explore projects in the field of computational linguistics, computer vision, machine translation, pattern recognition and many more Insightful projects to master deep learning and neural network architectures using Python and Keras Key Features Explore deep learning across computer vision, natural language processing (NLP), and image processing Discover best practices for the training of deep neural networks and their deployment Access popular deep learning models as well as widely used neural network architectures Book DescriptionDeep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system. Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects. By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way What you will learn Set up a deep learning development environment on Amazon Web Services (AWS) Apply GPU-powered instances as well as the deep learning AMI Implement seq-to-seq networks for modeling natural language processing (NLP) Develop an end-to-end speech recognition system Build a system for pixel-wise semantic labeling of an image Create a system that generates images and their regions Who this book is forPython Deep Learning Projects is for you if you want to get insights into deep learning, data science, and artificial intelligence. This book is also for those who want to break into deep learning and develop their own AI projects. It is assumed that you have sound knowledge of Python programming
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Python Deep Learning Projects book will simplify and ease how deep learning works, and demonstrate how neural networks play a vital role in exploring predictive analytics across different domains. You will explore projects in the field of computational linguistics, computer vision, machine translation, pattern recognition and many more Insightful projects to master deep learning and neural network architectures using Python and Keras Key Features Explore deep learning across computer vision, natural language processing (NLP), and image processing Discover best practices for the training of deep neural networks and their deployment Access popular deep learning models as well as widely used neural network architectures Book DescriptionDeep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system. Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects. By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way What you will learn Set up a deep learning development environment on Amazon Web Services (AWS) Apply GPU-powered instances as well as the deep learning AMI Implement seq-to-seq networks for modeling natural language processing (NLP) Develop an end-to-end speech recognition system Build a system for pixel-wise semantic labeling of an image Create a system that generates images and their regions Who this book is forPython Deep Learning Projects is for you if you want to get insights into deep learning, data science, and artificial intelligence. This book is also for those who want to break into deep learning and develop their own AI projects. It is assumed that you have sound knowledge of Python programming
Python Deep Learning Projects book will simplify and ease how deep learning works, and demonstrate how neural networks play a vital role in exploring predictive analytics across different domains. You will explore projects in the field of computational linguistics, computer vision, machine translation, pattern recognition and many more Insightful projects to master deep learning and neural network architectures using Python and Keras Key Features Explore deep learning across computer vision, natural language processing (NLP), and image processing Discover best practices for the training of deep neural networks and their deployment Access popular deep learning models as well as widely used neural network architectures Book DescriptionDeep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system. Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects. By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way What you will learn Set up a deep learning development environment on Amazon Web Services (AWS) Apply GPU-powered instances as well as the deep learning AMI Implement seq-to-seq networks for modeling natural language processing (NLP) Develop an end-to-end speech recognition system Build a system for pixel-wise semantic labeling of an image Create a system that generates images and their regions Who this book is forPython Deep Learning Projects is for you if you want to get insights into deep learning, data science, and artificial intelligence. This book is also for those who want to break into deep learning and develop their own AI projects. It is assumed that you have sound knowledge of Python programming
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originally posted on packtpub.com
Writer | Matthew Lamons, Rahul Kumar, Abhishek Nagaraja |
Dimensions | 9.3 x 7.5 centimetres (0.80 kg) |
Updated about 14 hours ago
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Writer | Matthew Lamons, Rahul Kumar, Abhishek Nagaraja |
Dimensions | 9.3 x 7.5 centimetres (0.80 kg) |