Ebooki
Natura umysłów. Jak zrozumieć świadomość
Daniel C. Dennett
Wybitny filozof Daniel C. Dennett, poszukując odpowiedzi na pytania o naturę naszego umysłu, łączy idee z zakresu filozofii, sztucznej inteligencji i neurobiologii. Starając się zrozumieć świadomość, stawia szereg intrygujących, a czasem wręcz niepokojących pytań. Czy możemy wiedzieć, co naprawdę dzieje się w umyśle innego człowieka? Czy to możliwe, że jesteś jedynym umysłem we Wszechświecie, a wszystko poza tobą jest jedynie bezwiednym mechanizmem? Autor dowodzi, jak bardzo skomplikowaną materią jest umysł człowieka – utkany z wielu różnych wątków i łączący wiele różnych wzorów. Niektóre z nich są tak stare jak samo życie, inne tak nowe jak dzisiejsza technologia. Umysł człowieka jest pod wieloma względami dokładnie taki jak umysły zwierząt, pod innymi całkowicie się od nich różni. Dzięki tej książce dostrzeżemy ścieżki, jakimi można podążyć, i pułapki, których należy unikać w naszych nieustających eksploracjach natury umysłów.
Natura w twórczym rozwoju i arteterapii
Wiesław Karolak
NATURA w twórczym rozwoju i arteterapii powstała - podobnie jak poprzednie książki z tej serii - z chęci podzielenia się doświadczeniami Autora z pracy artystycznej, pedagogicznej i arteterapeutycznej związanej z istotą kształtowania się świadomości - podmiotowości człowieka. Książka jest ofertą dla nauczycieli, metodyków, arteterapeutów, ale również dla studentów wielu specjalności pedagogicznych, edukacji artystycznej i arteterapii. Korzystać z niej, jak z przewodnika, będą mogli wszyscy, którzy prowadząc grupy, poszukują prostych i atrakcyjnych metod pracy dającej uczestnikom radość tworzenia i efektywność działań twórczych.
Natural Combat - Poradnik rozwoju poprzez trening sztuki walki i autosugestii
Bogusław Sztorc, Robert Świrad
Czym poradnik jest:1. Zwróceniem uwagi, że trening sztuki walki może być doskonałą i uniwersalną formą gimnastyczną.2.Przewodnikiem jak wydobyć naturalne i intuicyjne odruchy sztuki walki, tkwiące w każdym człowieku. 3.Drogowskazem podstawowych zasad sztuki walki.4.Spojrzeniem na tradycję wielu pokoleń uprawiających sztuki walki z wykorzystaniem ich do naturalnego rozwoju fizycznego i psychicznego.5.Analizą skutecznych metod walki opartą na wielu istniejących systemach.6.Elementem poznawczym prostych technik synchronizacji ciała i umysłu.7.Pochwałą różnorodności technik sztuki walki i autosugestii, z których każdy może wybrać coś dla siebie, w zależności od swoich potrzeb i predyspozycji psycho-fizycznych.Czym poradnik nie jest:1.Nie jest panaceum zostania mistrzem sztuk walki.2.Nie stanowi opozycji do stylowych sztuk walki.3.Nie jest odrębnym stylem narzucającym nowe zasady, taktykę walki, techniki itd.Sama nazwa Natural Combat nie jest nazwą nowego systemu walki, jest jedynie określeniem naturalności w sztuce walki i określeniem pewnych zasad, bez podziału na style. Jest pewną przestrzenią, w której można się poruszać, bez względu na uprawianie konkretnych i tradycyjnych stylów walki. Wynika z zainteresowania autorów autentycznymi systemami walki, istniejącymi nie tylko na Dalekim Wschodzie ale również na całym świecie. Autorzy nie tworzą nowej organizacji z określonymi wymaganiami a jedynie pomoc w rozszerzeniu możliwości własnego stylu lub intuicyjnego zastosowania technik walki.Bogusław SztorcUrodzony w 1962r., z wykształcenia inżynier, absolwent Politechniki Śląskiej w Katowicach.Posiada zamiłowanie do poszukiwania innowacyjnych rozwiązań technicznych. Przez wiele lat był zawodnikiem karate sportowego, biorąc udział w zawodach sportowych, instruktor karate, posiada 1 Dan karate Shotokan, szukający inspiracji w wielu systemach sztuk walki całego świata.Zainteresowany różnymi nurtami filozoficznymi i kulturowymi także systemami leczniczymi w tym Ajurwedą i Tradycyjną Medycyną Chińską.Praktykuje Qi - Gong chińską sztukę zachowania zdrowia i sprawności fizycznej.Lubi również jazdę na rowerze.Robert ŚwiradUrodzony w 1962r., z wykształcenia inżynier, absolwent Politechniki Śląskiej w Katowicach.Weteran sztuk walki z 35-letnim stażem, ekspert w kilku dyscyplinach, zarówno w stylach walki jak i systemach zdrowotnych. Rozpoczął trening jako 16-latek, uprawiając początkowo japońskie style takie jak Karate Kyokushin, Jujutsu a następnie Karate Shotokan zdobywając stopień 1 Dan oraz kwalifikacje instruktora karate. Przez wiele lat był czynnym zawodnikiem karate sportowego biorąc udział w turniejach krajowych i międzynarodowych. W latach 80-tych pracował zawodowo jako instruktor sztuk walki w dużym klubie sportowym prowadząc treningi zarówno dla początkujących jak i zawodników. Równolegle z działalnością sportowa uprawiał również hinduska Hatha Jogę oraz ćwiczenia medytacyjne. W roku 1992 wyemigrował do Australii gdzie kontynuował trening karate Shotokan a takze Shito-ryu uzyskujac stopien 3 Dan. Dążenie do poznania źródeł tych systemów zrodziło po latach zainteresowanie okinawskimi stylami walki, którymi zajmował się przez kilka kolejnych lat uzyskując stopień 4 Dan. Od roku 2000 uprawia chińskie style Kung Fu z południowej prowincji Fujian oryginalne korzenie systemów okinawskich. Od 5-ciu lat intensywnie uprawia również brazylijska sztukę walki Capoeira oraz prowadzi własne zajęcia w systemie Combat i Street Self Defence. W treningu indywidualnym koncentruje się na Qi - Gong chińskiej sztuce zachowania zdrowia i sprawności fizycznej a także elementach Tai Chi. Jest również entuzjasta nowoczesnego fitnessu, w którym posiada kwalifikacje instruktora. Jako uzupełnienie treningu sprawnościowego regularnie ćwiczy z obciążeniami a w szczególności z odważnikami kulowymi - ketttlebells. Wysoka sprawność fizyczna i dobre zdrowie zawdzięcza nie tylko odpowiednio dobranemu treningowi fizycznemu ale również ćwiczeniom medytacji oraz stosowaniu Tradycyjnej Medycyny Chińskiej.
Brian Sacash, Bhargav Srinivasa-Desikan, Reddy Anil Kumar
Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data.This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy.You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning.This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis.
Mercury Learning and Information, Oswald Campesato
This book introduces developers to basic concepts in NLP and machine learning, providing numerous code samples to support the topics covered. The journey begins with introductory material on NumPy and Pandas, essential for data manipulation. Following this, chapters delve into NLP concepts, algorithms, and toolkits, providing a solid foundation in natural language processing.As you progress, the book covers machine learning fundamentals and classifiers, demonstrating how these techniques are applied in NLP. Practical examples using TF2 and Keras illustrate how to implement various NLP tasks. Advanced topics include the Transformer architecture, BERT-based models, and the GPT family of models, showcasing the latest advancements in the field.The final chapters and appendices offer a comprehensive overview of related topics, including data and statistics, Python3, regular expressions, and data visualization with Matplotlib and Seaborn. Companion files with source code and figures ensure a hands-on learning experience. This book equips you with the knowledge and tools needed to excel in NLP and machine learning.
Sohom Ghosh , Dwight Gunning
If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems.You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language.
Mercury Learning and Information, Oswald Campesato
This book is for developers seeking an overview of basic concepts in Natural Language Processing (NLP). It caters to those with varied technical backgrounds, offering numerous code samples and listings to illustrate the wide range of topics covered. The journey begins with managing data relevant to NLP, followed by two chapters on fundamental NLP concepts. This foundation is reinforced with Python code samples that bring these concepts to life.The book then delves into practical NLP applications, such as sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and chatbots. These examples provide real-world context and demonstrate how NLP techniques can be applied to solve common problems. The final chapter introduces advanced topics, including the Transformer architecture, BERT-based models, and the GPT family, highlighting the latest state-of-the-art developments in the field.Appendices offer additional resources, including Python code samples on regular expressions and probability/statistical concepts, ensuring a well-rounded understanding. Companion files with source code and figures enhance the learning experience, making this book a comprehensive guide for mastering NLP techniques and applications.
Natural Language Processing: Python and NLTK. Click here to enter text
Jacob Perkins, Nitin Hardeniya, Deepti Chopra, Iti...
Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it’s becoming imperative that computers comprehend all major natural languages. The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy.The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods. The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python.This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products:? NTLK essentials by Nitin Hardeniya? Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins? Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur
Mercury Learning and Information, Oswald Campesato
This book is for developers seeking an overview of basic concepts in Natural Language Processing (NLP). It caters to a technical audience, offering numerous code samples and listings to illustrate the wide range of topics covered. The journey begins with managing data relevant to NLP, followed by two chapters on fundamental NLP concepts. This foundation is reinforced with Python code samples that bring these concepts to life.The book then delves into practical NLP applications, such as sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and chatbots. These examples provide real-world context and demonstrate how NLP techniques can be applied to solve common problems. The final chapter introduces advanced topics, including the Transformer architecture, BERT-based models, and the GPT family, highlighting the latest state-of-the-art developments in the field.Appendices offer additional resources, including Python code samples on regular expressions and probability/statistical concepts, ensuring a well-rounded understanding. Companion files with source code and figures enhance the learning experience, making this book a comprehensive guide for mastering NLP techniques and applications.
Mona M, Premkumar Rangarajan
Natural language processing (NLP) uses machine learning to extract information from unstructured data. This book will help you to move quickly from business questions to high-performance models in production.To start with, you'll understand the importance of NLP in today’s business applications and learn the features of Amazon Comprehend and Amazon Textract to build NLP models using Python and Jupyter Notebooks. The book then shows you how to integrate AI in applications for accelerating business outcomes with just a few lines of code. Throughout the book, you'll cover use cases such as smart text search, setting up compliance and controls when processing confidential documents, real-time text analytics, and much more to understand various NLP scenarios. You'll deploy and monitor scalable NLP models in production for real-time and batch requirements. As you advance, you'll explore strategies for including humans in the loop for different purposes in a document processing workflow. Moreover, you'll learn best practices for auto-scaling your NLP inference for enterprise traffic.Whether you're new to ML or an experienced practitioner, by the end of this NLP book, you'll have the confidence to use AWS AI services to build powerful NLP applications.
Tadej Magajna
Flair is an easy-to-understand natural language processing (NLP) framework designed to facilitate training and distribution of state-of-the-art NLP models for named entity recognition, part-of-speech tagging, and text classification. Flair is also a text embedding library for combining different types of embeddings, such as document embeddings, Transformer embeddings, and the proposed Flair embeddings.Natural Language Processing with Flair takes a hands-on approach to explaining and solving real-world NLP problems. You'll begin by installing Flair and learning about the basic NLP concepts and terminology. You will explore Flair's extensive features, such as sequence tagging, text classification, and word embeddings, through practical exercises. As you advance, you will train your own sequence labeling and text classification models and learn how to use hyperparameter tuning in order to choose the right training parameters. You will learn about the idea behind one-shot and few-shot learning through a novel text classification technique TARS. Finally, you will solve several real-world NLP problems through hands-on exercises, as well as learn how to deploy Flair models to production.By the end of this Flair book, you'll have developed a thorough understanding of typical NLP problems and you’ll be able to solve them with Flair.
Krishna Dayanidhi
This book is for experienced Java developers with NLP needs, whether academics, industrialists, or hobbyists. A basic knowledge of NLP terminology will be beneficial.
Richard M. Reese
Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon Web Services (AWS). You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentence, or semantic word.
Richard M. Reese , Richard M Reese
If you are a Java programmer who wants to learn about the fundamental tasks underlying natural language processing, this book is for you. You will be able to identify and use NLP tasks for many common problems, and integrate them in your applications to solve more difficult problems. Readers should be familiar/experienced with Java software development.
Richard M. Reese, AshishSingh Bhatia
Natural Language Processing (NLP) allows you to take any sentence and identify patterns, special names, company names, and more. The second edition of Natural Language Processing with Java teaches you how to perform language analysis with the help of Java libraries, while constantly gaining insights from the outcomes.You’ll start by understanding how NLP and its various concepts work. Having got to grips with the basics, you’ll explore important tools and libraries in Java for NLP, such as CoreNLP, OpenNLP, Neuroph, and Mallet. You’ll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts-of-speech and parsing trees. You’ll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and more.By the end of this book, you’ll have learned more about NLP, neural networks, and various other trained models in Java for enhancing the performance of NLP applications.
Cuantum Technologies LLC
Embark on a comprehensive journey to master natural language processing (NLP) with Python. Begin with foundational concepts like text preprocessing, tokenization, and key Python libraries such as NLTK, spaCy, and TextBlob. Explore the challenges of text data and gain hands-on experience in cleaning, tokenizing, and building basic NLP pipelines. Early chapters provide practical exercises to solidify your understanding of essential techniques.Advance to sophisticated topics like feature engineering using Bag of Words, TF-IDF, and embeddings like Word2Vec and BERT. Delve into language modeling with RNNs, syntax parsing, and sentiment analysis, learning to apply these techniques in real-world scenarios. Chapters on topic modeling and text summarization equip you to extract insights from data, while transformer-based models like BERT take your skills to the next level. Each concept is paired with Python-based examples, ensuring practical mastery.The final chapters focus on real-world projects, such as developing chatbots, sentiment analysis dashboards, and news aggregators. These hands-on applications challenge you to design, train, and deploy robust NLP solutions. With its structured approach and practical focus, this book equips you to confidently tackle real-world NLP challenges and innovate in the field.