Hands On Natural Language Processing With Tensorflow
DOWNLOAD
Download Hands On Natural Language Processing With Tensorflow PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Hands On Natural Language Processing With Tensorflow book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Hands On Natural Language Processing With Tensorflow
DOWNLOAD
Author : Michael Walker
language : en
Publisher:
Release Date : 2018-07-31
Hands On Natural Language Processing With Tensorflow written by Michael Walker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with categories.
***** BUY NOW (will soon return to 24.97 $) ***** MONEY BACK GUARANTEE BY AMAZON (See Below FAQ) ***** *** Free eBook for customers who purchase the print book from Amazon *** Are you thinking of learning more Natural Language Processing (NLP) using TensorFlow? This book is for you. It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions.This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using ̈NLP. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses.To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach which would lead to better mental representations. Target Users The book designed for a variety of target audiences. The most suitable users would include: Anyone who is intrigued by how algorithms arrive at predictions but has no previous knowledge of the field. Software developers and engineers with a strong programming background but seeking to break into the field of Data Science and NLP. Seasoned professionals in the field of artificial intelligence and machine learning who desire a bird's eye view of current techniques and approaches. What's Inside This Book? Introduction to Natural Language Processing What is Natural Language Processing Perspectivizing NLP: Areas of AI and Their Interdependencies Purpose of Natural Language Processing Text Manipulation Tokenization Stemming Lemmatization Normalization Accessing Text Corpora and Lexical Resources Processing Raw Text Categorizing and Tagging Words NLP Applications Text Classification Sentiment Classification Topic Modelling Question Answering Speech Recognition Machine Translation Word Representation Bag of Words One-Hot Encoding Word Vectors Representation Word2Vec and GloVe Learning to Classify Text Supervised Classification Decision Trees Naive Bayes Classifiers Maximum Entropy Classifiers Deep Learning for NLP What is Deep Learning Feed Forward Neural Networks Recurrent Neural Networks Gated Recurrent Unit Long Short Term Memory Language Processing and Python using NLTK Introduction to TensorFlow Text Classification Frequently Asked Questions Q: Is this book for me and do I need programming experience?A: If you want to smash NLP from scratch, this book is for you. If you already wrote a few lines of code and recognize basic programming statements, you'll be OK.Q: Does this book include everything I need to become a NLP expert?A: Unfortunately, no. This book is designed for readers taking their first steps in NLP and further learning will be required beyond this book to master all aspects of NLP.Q: Can I have a refund if this book doesn't fit for me?A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email at contact@aisciences.net.
Hands On Natural Language Processing With Python
DOWNLOAD
Author : Rajesh Arumugam
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-07-18
Hands On Natural Language Processing With Python written by Rajesh Arumugam and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-18 with Computers categories.
Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.
Natural Language Processing With Tensorflow
DOWNLOAD
Author : Thushan Ganegedara
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-31
Natural Language Processing With Tensorflow written by Thushan Ganegedara and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-31 with Computers categories.
Write modern natural language processing applications using deep learning algorithms and TensorFlow Key Features Focuses on more efficient natural language processing using TensorFlow Covers NLP as a field in its own right to improve understanding for choosing TensorFlow tools and other deep learning approaches Provides choices for how to process and evaluate large unstructured text datasets Learn to apply the TensorFlow toolbox to specific tasks in the most interesting field in artificial intelligence Book Description Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks. Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator. After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks. What you will learn Core concepts of NLP and various approaches to natural language processing How to solve NLP tasks by applying TensorFlow functions to create neural networks Strategies to process large amounts of data into word representations that can be used by deep learning applications Techniques for performing sentence classification and language generation using CNNs and RNNs About employing state-of-the art advanced RNNs, like long short-term memory, to solve complex text generation tasks How to write automatic translation programs and implement an actual neural machine translator from scratch The trends and innovations that are paving the future in NLP Who this book is for This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as some knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required, although some background in NLP or computational linguistics will be helpful.
Natural Language Processing Crash Course For Beginners
DOWNLOAD
Author : Ai Publishing
language : en
Publisher:
Release Date : 2020-08-04
Natural Language Processing Crash Course For Beginners written by Ai Publishing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-04 with categories.
Natural Language Processing Crash Course for Beginners Artificial Intelligence (AI) isn't the latest fad! The reason is AI has been around since 1956, and its relevance is evident in every field today. Artificial Intelligence incorporates human intelligence into machines. Machine Learning (ML), a branch of AI, enables machines to learn by themselves. Deep Learning (DL), a subfield of Machine Learning, uses algorithms that are inspired by the functioning of the human brain. Natural Language Processing (NLP) combines computational linguistics and Artificial Intelligence, enabling computers and humans to communicate seamlessly. And NLP is immensely powerful and impactful as every business is looking to integrate it into their day to day dealings. How Is This Book Different? This book by AI Publishing is carefully crafted, giving equal importance to the theoretical concepts as well as the practical aspects of natural language processing. In each chapter of the second half of the book, the theoretical concepts of different types of deep learning and NLP techniques have been covered in-depth, followed by practical examples. You will learn how to apply different NLP techniques using the TensorFlow and Keras libraries for Python. Each chapter contains exercises that are designed to evaluate your understanding of the concepts covered in that chapter. Also, in the Resources section of each chapter, you can access the Python notebook. The author has also compiled a list of hands-on NLP projects and competitions that you can try on your own. The main benefit of purchasing this book is you get immediate access to all the extra learning material presented with this book--Python codes, exercises, PDFs, and references--on the publisher's website without having to spend an extra cent. You can download the datasets used in this book at runtime, or you can access them in the Resources/Datasets folder. The author holds your hand through everything. He provides you a step by step explanation of the installation of the software needed to implement the various NLP techniques in this book. You can start experimenting with the practical aspects of NLP right from the beginning. Even if you are new to Python, you'll find the ultra-short course on Python programming language in the second chapter immensely helpful. You get all the codes and datasets with this book. So, if you have access to a computer with the internet, you can get started. The topics covered include: What is Natural Language Processing? Environment Setup and Python Crash Course Introduction to Deep Learning Text Cleaning and Manipulation Common NLP Tasks Importing Text Data from Various Sources Word Embeddings: Converting Words to Numbers IMDB Movies Sentimental Analysis Ham and Spam Message Classification Text Summarization and Topic Modeling Text Classification with Deep Learning Text Translation Using Seq2Seq Model State of the Art NLP with BERT Transformers Hands-on NLP Projects/Articles for Practice Exercise Solutions Click the BUY button and download the book now to start your Natural Language Processing journey.
Natural Language Processing With Tensorflow
DOWNLOAD
Author : Thushan Ganegedara
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-07-29
Natural Language Processing With Tensorflow written by Thushan Ganegedara and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-29 with Computers categories.
From introductory NLP tasks to Transformer models, this new edition teaches you to utilize powerful TensorFlow APIs to implement end-to-end NLP solutions driven by performant ML (Machine Learning) models Key Features • Learn to solve common NLP problems effectively with TensorFlow 2.x • Implement end-to-end data pipelines guided by the underlying ML model architecture • Use advanced LSTM techniques for complex data transformations, custom models and metrics Book Description Learning how to solve natural language processing (NLP) problems is an important skill to master due to the explosive growth of data combined with the demand for machine learning solutions in production. Natural Language Processing with TensorFlow, Second Edition, will teach you how to solve common real-world NLP problems with a variety of deep learning model architectures. The book starts by getting readers familiar with NLP and the basics of TensorFlow. Then, it gradually teaches you different facets of TensorFlow 2.x. In the following chapters, you then learn how to generate powerful word vectors, classify text, generate new text, and generate image captions, among other exciting use-cases of real-world NLP. TensorFlow has evolved to be an ecosystem that supports a machine learning workflow through ingesting and transforming data, building models, monitoring, and productionization. We will then read text directly from files and perform the required transformations through a TensorFlow data pipeline. We will also see how to use a versatile visualization tool known as TensorBoard to visualize our models. By the end of this NLP book, you will be comfortable with using TensorFlow to build deep learning models with many different architectures, and efficiently ingest data using TensorFlow Additionally, you'll be able to confidently use TensorFlow throughout your machine learning workflow. What you will learn • Learn core concepts of NLP and techniques with TensorFlow • Use state-of-the-art Transformers and how they are used to solve NLP tasks • Perform sentence classification and text generation using CNNs and RNNs • Utilize advanced models for machine translation and image caption generation • Build end-to-end data pipelines in TensorFlow • Learn interesting facts and practices related to the task at hand • Create word representations of large amounts of data for deep learning Who this book is for This book is for Python developers and programmers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required.
Deep Learning Essentials
DOWNLOAD
Author : Anurag Bhardwaj
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-01-30
Deep Learning Essentials written by Anurag Bhardwaj and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-30 with Computers categories.
Get to grips with the essentials of deep learning by leveraging the power of Python Key Features Your one-stop solution to get started with the essentials of deep learning and neural network modeling Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner Book Description Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more. This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications. What you will learn Get to grips with the core concepts of deep learning and neural networks Set up deep learning library such as TensorFlow Fine-tune your deep learning models for NLP and Computer Vision applications Unify different information sources, such as images, text, and speech through deep learning Optimize and fine-tune your deep learning models for better performance Train a deep reinforcement learning model that plays a game better than humans Learn how to make your models get the best out of your GPU or CPU Who this book is for Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python.
Natural Language Processing With Tensorflow
DOWNLOAD
Author : Thushan Ganegedara
language : en
Publisher: Packt Publishing
Release Date : 2022-07-29
Natural Language Processing With Tensorflow written by Thushan Ganegedara and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-29 with categories.
From introductory NLP tasks to Transformer models, this new edition teaches you to utilize powerful TensorFlow APIs to implement end-to-end NLP solutions driven by performant ML (Machine Learning) models Key Features: Learn to solve common NLP problems effectively with TensorFlow 2.x Implement end-to-end data pipelines guided by the underlying ML model architecture Use advanced LSTM techniques for complex data transformations, custom models and metrics Book Description: Learning how to solve natural language processing (NLP) problems is an important skill to master due to the explosive growth of data combined with the demand for machine learning solutions in production. Natural Language Processing with TensorFlow, Second Edition, will teach you how to solve common real-world NLP problems with a variety of deep learning model architectures. The book starts by getting readers familiar with NLP and the basics of TensorFlow. Then, it gradually teaches you different facets of TensorFlow 2.x. In the following chapters, you then learn how to generate powerful word vectors, classify text, generate new text, and generate image captions, among other exciting use-cases of real-world NLP. TensorFlow has evolved to be an ecosystem that supports a machine learning workflow through ingesting and transforming data, building models, monitoring, and productionization. We will then read text directly from files and perform the required transformations through a TensorFlow data pipeline. We will also see how to use a versatile visualization tool known as TensorBoard to visualize our models. By the end of this NLP book, you will be comfortable with using TensorFlow to build deep learning models with many different architectures, and efficiently ingest data using TensorFlow Additionally, you'll be able to confidently use TensorFlow throughout your machine learning workflow. What You Will Learn: Learn core concepts of NLP and techniques with TensorFlow Use statee-of-the-art Transformers and how they are used to solve NLP tasks Perform sentence classification and text generation using CNNs and RNNS Utilize advanced models for machine translation and image caption generation Build end-to-end data pipelines in TensorFlow Learn interesting facts and practices related to the task at hand Create word representations of large amounts of data for deep learning Who this book is for: This book is for Python developers and programmers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required.
Hands On Transfer Learning With Python
DOWNLOAD
Author : Dipanjan Sarkar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-08-31
Hands On Transfer Learning With Python written by Dipanjan Sarkar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-31 with Computers categories.
Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem Key Features Build deep learning models with transfer learning principles in Python implement transfer learning to solve real-world research problems Perform complex operations such as image captioning neural style transfer Book Description Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems. The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples. The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with practical examples. In the concluding chapters, we will focus on a multitude of real-world case studies and problems associated with areas such as computer vision, audio analysis and natural language processing (NLP). By the end of this book, you will be able to implement both DL and transfer learning principles in your own systems. What you will learn Set up your own DL environment with graphics processing unit (GPU) and Cloud support Delve into transfer learning principles with ML and DL models Explore various DL architectures, including CNN, LSTM, and capsule networks Learn about data and network representation and loss functions Get to grips with models and strategies in transfer learning Walk through potential challenges in building complex transfer learning models from scratch Explore real-world research problems related to computer vision and audio analysis Understand how transfer learning can be leveraged in NLP Who this book is for Hands-On Transfer Learning with Python is for data scientists, machine learning engineers, analysts and developers with an interest in data and applying state-of-the-art transfer learning methodologies to solve tough real-world problems. Basic proficiency in machine learning and Python is required.
Transformers For Natural Language Processing
DOWNLOAD
Author : Denis Rothman
language : en
Publisher:
Release Date : 2021-01-28
Transformers For Natural Language Processing written by Denis Rothman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-28 with categories.
Become an AI language understanding expert by mastering the quantum leap of Transformer neural network models Key Features Build and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using concepts that outperform classical deep learning models Go through hands-on applications in Python using Google Colaboratory Notebooks with nothing to install on a local machine Learn training tips and alternative language understanding methods to illustrate important key concepts Book Description The transformer architecture has proved to be revolutionary in outperforming the classical RNN and CNN models in use today. With an apply-as-you-learn approach, Transformers for Natural Language Processing investigates in vast detail the deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question answering, and many more NLP domains with transformers. The book takes you through NLP with Python and examines various eminent models and datasets within the transformer architecture created by pioneers such as Google, Facebook, Microsoft, OpenAI, and Hugging Face. The book trains you in three stages. The first stage introduces you to transformer architectures, starting with the original transformer, before moving on to RoBERTa, BERT, and DistilBERT models. You will discover training methods for smaller transformers that can outperform GPT-3 in some cases. In the second stage, you will apply transformers for Natural Language Understanding (NLU) and Natural Language Generation (NLG). Finally, the third stage will help you grasp advanced language understanding techniques such as optimizing social network datasets and fake news identification. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models by tech giants to various datasets. What You Will Learn Use the latest pretrained transformer models Grasp the workings of the original Transformer, GPT-2, BERT, T5, and other transformer models Create language understanding Python programs using concepts that outperform classical deep learning models Use a variety of NLP platforms, including Hugging Face, Trax, and AllenNLP Apply Python, TensorFlow, and Keras programs to sentiment analysis, text summarization, speech recognition, machine translations, and more Measure productivity of key transformers to define their scope, potential, and limits, in production Who this book is for Since the book does not teach basic programming, you must be familiar with neural networks, Python, PyTorch, and TensorFlow in order to learn their implementation with Transformers. Readers who can benefit the most from this book include deep learning & NLP practitioners, data analysts and data scientists who want an introduction to AI language understanding to process the increasing amounts of language-driven functions.
Hands On Neural Networks
DOWNLOAD
Author : Leonardo De Marchi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-30
Hands On Neural Networks written by Leonardo De Marchi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-30 with Computers categories.
Design and create neural networks with deep learning and artificial intelligence principles using OpenAI Gym, TensorFlow, and Keras Key FeaturesExplore neural network architecture and understand how it functionsLearn algorithms to solve common problems using back propagation and perceptronsUnderstand how to apply neural networks to applications with the help of useful illustrationsBook Description Neural networks play a very important role in deep learning and artificial intelligence (AI), with applications in a wide variety of domains, right from medical diagnosis, to financial forecasting, and even machine diagnostics. Hands-On Neural Networks is designed to guide you through learning about neural networks in a practical way. The book will get you started by giving you a brief introduction to perceptron networks. You will then gain insights into machine learning and also understand what the future of AI could look like. Next, you will study how embeddings can be used to process textual data and the role of long short-term memory networks (LSTMs) in helping you solve common natural language processing (NLP) problems. The later chapters will demonstrate how you can implement advanced concepts including transfer learning, generative adversarial networks (GANs), autoencoders, and reinforcement learning. Finally, you can look forward to further content on the latest advancements in the field of neural networks. By the end of this book, you will have the skills you need to build, train, and optimize your own neural network model that can be used to provide predictable solutions. What you will learnLearn how to train a network by using backpropagationDiscover how to load and transform images for use in neural networksStudy how neural networks can be applied to a varied set of applicationsSolve common challenges faced in neural network developmentUnderstand the transfer learning concept to solve tasks using Keras and Visual Geometry Group (VGG) networkGet up to speed with advanced and complex deep learning concepts like LSTMs and NLP Explore innovative algorithms like GANs and deep reinforcement learningWho this book is for If you are interested in artificial intelligence and deep learning and want to further your skills, then this intermediate-level book is for you. Some knowledge of statistics will help you get the most out of this book.