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Secrets of Neuro-Linguistic Programming
THESE ARE THE REAL NLP INSIGHTS YOU NEED TO SUCCEEDWHAT ARE THE 50 SECRETS THE NLP MASTERS KNOW? Do they have a secret recipe for success? Is there a special alchemy? NLP can help you change your life, overcome obstacles and achieve your goals, but not everyone is successful. Secrets of Neuro-Linguistic Programming reveals the things you need to know to use NLP effectively. Every one of the 50 secrets in this book contains 3 strategies you can put into practice right now to get better results. Some of the ideas will surprise you, all will inspire you. Put these simple strategies together and you have a recipe for success, a formula that will unlock your full potential.Change your life with Neuro-Linguistic ProgrammingFundamental to NLP is the idea of modelling excellence: the idea that, if someone else can do a thing, then by coding it, you can do that thing too. Secrets of Neuro-Linguistic Programming supports you on your journey to mastering NLP by sharing the insights from the greatest NLP writers, trainers, therapists, and coaches in the field.Discover the essential presuppositions you need to hold in order to banish limiting beliefs. Find the chapters that relate best to the outcome you're looking for. Each chapter gives examples of how to apply the techniques for a successful result whether that be in business, parenting, relationships, health, sport or any other aspect of life. Whatever your goals, this book provides the tools and techniques you need to get there. With nuggets of wisdom gathered over years of experience, it gives you everything you need to know to succeed.ABOUT THE SERIESSecrets books are designed to be easy to incorporate into your daily life. They boil down the essentials of important topics into short, quick lessons giving expert advice on a wide range of challenges that you can apply instantly. Each chapter outlines one of the 50 secrets and gives three strategies for putting the ideas into action. Whether you want to improve your efficiency, clear your desk, or be on top of your work, these books give the answers you're looking for.
R 395.00
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Python Data Science Handbook
Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all—IPython, NumPy, pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you'll learn how:IPython and Jupyter provide computational environments for scientists using PythonNumPy includes the ndarray for efficient storage and manipulation of dense data arraysPandas contains the DataFrame for efficient storage and manipulation of labeled/columnar dataMatplotlib includes capabilities for a flexible range of data visualizationsScikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithms
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Python in a Nutshell
Python was recently ranked as today's most popular programming language on the TIOBE index, thanks to its broad applicability to design and prototyping to testing, deployment, and maintenance. With this updated fourth edition, you'll learn how to get the most out of Python, whether you're a professional programmer or someone who needs this language to solve problems in a particular field.Carefully curated by recognized experts in Python, this new edition focuses on version 3.10, bringing this seminal work on the Python language fully up to date on five version releases, including preview coverage of upcoming 3.11 features.This handy guide will help you:Learn how Python represents data and program as objectsUnderstand the value and uses of type annotationsExamine which language features appeared in which recent versionsDiscover how to use modern Python idiomaticallyLearn ways to structure Python projects appropriatelyUnderstand how to debug Python code
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Python Scripting for Computational Science
With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language. All the tools and examples in this book are open source codes. This third edition features lots of new material. It is also released after a comprehensive reorganization of the text. The author has inserted improved examples and tools and updated information, as well as correcting any errors that crept in to the first imprint.
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Introduction to Python for Humanists
This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language, and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates, graduates, and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python, allowing them to engage with more advanced textbooks. This book fills a real need, as it is first Python introduction to be aimed squarely at humanities students, as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it, in addition to allowing those who are interested in being self-taught can use it for that purpose.Key Features: Data analysis Data science Computational humanities Digital humanities Python Natural language processing Social network analysisApp development
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CPython
Deep Dive CPython explores the internal mechanics of CPython, the widely used Python interpreter written in C. Starting with a practical guide on downloading and compiling the CPython source, this book is perfect for developers eager to understand Python's behaviour at a fundamental level. The book takes readers from basic concepts to complex details with a systematic breakdown of core components. It covers everything from CPython's data structures like PyObject and PyTypeObject to object lifecycle management, giving insight into memory allocation and object reference counting. Each chapter illustrates CPython's architecture, such as Python's "everything is an object" philosophy, list handling, string manipulation, and dictionary operations. Readers will explore Python's REPL modifications, string internals, and custom type creation with practical examples, like crafting a "backflipping" PyKittyType. Detailed sections on Python's virtual machine operations, bytecode generation, and exception handling enrich readers' understanding of how Python code is parsed, compiled, and executed. This book is a thorough guide for readers who want to go beyond basic Python use and understand how it works internally. Covering complex concepts like generators, iterators, descriptors, and metaclasses, this book equips readers with a thorough grasp of Python's performance optimization and design complexities. What you will learn: How to download, compile, and modify CPython's source codeGain insight into fundamental structures like PyObject and PyTypeObject, Understand Python's detailed handling of lists, strings, dictionaries, and the REPL environment.What are bytecode generation, custom types, and the inner workings of Python's virtual machine. Who this book is for: Python programmers aiming to gain a deeper understanding of Python's internals and move beyond standard usage, as well as software professionals interested in CPython's C-based implementation and core architecture.
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Hands-On Blockchain for Python Developers
Write popular DeFi and NFT smart contracts with Vyper, a Pythonic programming language, and integrate blockchain with real-world applications using Python Key FeaturesUse the world's easiest programming language to build web3 applicationsWrite common smart contracts like decentralized exchanges, NFT marketplaces, and lending applicationsUnlock deeper levels of insights with technologies relating to blockchain, such as IPFS and Layer 2Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionWe are living in the age of decentralized fi nance and NFTs. People swap tokens on Uniswap, borrow assets from Aave, send payments with stablecoins, trade art NFTs on OpenSea, and more. To build applications of this kind, you need to know how to write smart contracts.This comprehensive guide will help you explore all the features of Vyper, a programming language designed to write smart contracts. You’ll also explore the web3.py library. As you progress, you’ll learn how to connect to smart contracts, read values, and create transactions. To make sure your foundational knowledge is strong enough, the book guides you through Ape Framework, which can help you create decentralized exchanges, NFT marketplaces, voting applications, and more. Each project provides invaluable insights and hands-on experience, equipping you with the skills you need to build real-world blockchain solutions.By the end of this book, you’ll be well versed with writing common Web3 applications such as a decentralized exchange, an NFT marketplace, a voting application, and more.What you will learnUnderstand blockchain and smart contractsLearn how to write smart contracts with VyperExplore how to use the web3.py library and Ape FrameworkDiscover related technologies such as Layer 2 and IPFSGain a step-by-step guide to writing an automated market maker (AMM) decentralized exchange (DEX) smart contractBuild innovative, interactive, and token-gated Web3 NFT applicationsWho this book is forThis blockchain book is for developers interested in understanding blockchain and smart contracts. It is suitable for both technology enthusiasts looking to explore blockchain technology and programmers who aspire to become smart contract engineers. Basic knowledge of GNU/Linux and Python programming is mandatory to get started with this book.
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BiteSize Python for Intermediate Learners
This book is an introduction to Python for intermediate learners. It allows readers to take a slow and steady approach to building upon their understanding of Python code. While there are many books, websites, and online courses about the topic, Python programming is broken down here into easily digestible lessons of less than 5 minutes each, following a tried and tested BiteSize approach.Each lesson begins with a clear and concise introduction to the topic, giving the reader a strong base to start from and gets them ready for deeper learning. This is followed by coding demonstrations that further explore the ideas discussed. The book offers practice tasks in different difficulty levels, so readers can test their knowledge and grow their confidence. The reader will also play with case studies to solve real-world problems. Tips on how to incorporate Generative AI into a learning toolkit are provided, for purposes like feedback, practice exercises, code reviews, and exploring advanced topics. Recommended AI prompts can help readers identify areas for improvement, review key concepts, and track progress.This book is designed for intermediate learners with a basic understanding of Python. It is ideal for individuals with busy schedules or limited time for studying.
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Beginning Python
Gain a fundamental understanding of Python’s syntax and features with this revised introductory and practical reference. Covering a wide array of Python–related programming topics, including addressing language internals, database integration, network programming, and web services, you’ll be guided by sound development principles. Updated to reflect the latest in Python programming paradigms and several of the most crucial features found in Python 3, Beginning Python, Fourth Edition also covers advanced topics such as extending Python and packaging/distributing Python applications. Ten accompanying projects will ensure you can get your hands dirty in no time. You will: Become a proficient Python programmer by following along with a friendly, practical guide to the language’s key featuresWrite code faster by learning how to take advantage of advanced features such as magic methods, exceptions, and abstractionGain insight into modern Python programming paradigms including testing, documentation, packaging, and distributionWork through several interesting projects, including a P2P file–sharing application, chat client, video game, remote text editor, and more Who This Book Is For Programmers, novice and otherwise, seeking a comprehensive introduction to the Python programming language.
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Handbook of NLP
Since its Californian beginnings a generation ago, Neurolinguistic Programming (NLP) has won world-wide recognition as probably the most powerful set of tools available for improving communication, thinking and problem-solving. Derived from the study of leading practitioners in fields as disparate as psychotherapy and selling, NLP is now used extensively in business, management, human resource development and sport. Dr Alder's Handbook brings together in one volume the ideas and skills involved in applying NLP to achieve superior performance at both the personal and the professional level. Part 1 sets out the underlying principles and introduces key concepts such as outcomes, representational systems, anchoring, modelling and reframing, together with the techniques required for putting them to work. Part 2 shows how to use NLP in training, selling, negotiating, interviewing, coaching and presentation. Throughout the text there are examples and exercises designed to help readers profit from, rather than simply understand, the procedures described. Other valuable features include a glossary of terms and a sources and resources section containing an annotated reading list and details of organizations offering NLP training. Anyone seeking a comprehensive guide to NLP theory and practice need look no further.
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What Counts as Evidence when Researching Neuro-Linguistic Programming in Education?
Discover a groundbreaking approach to transforming post-16 education with this engaging and insightful book by Dr. Voldis Kudliskis. Drawing on 25 years of teaching, action research and qualitative studies, this work explores the powerful impact of neuro-linguistic programming (NLP) as an education coaching philosophy. Unlike traditional academic texts, this book offers a lively, accessible look into how NLP can enhance students’ learning experiences, focusing on their voices and perceptions. Through real-world insights and practical coaching processes, the book reveals how teachers, and students themselves, can apply NLP techniques to foster motivation, confidence, and success in education. It’s a must-read for teachers, school leaders, and education professionals eager to innovate and improve post-16 education. Whether you’re looking to deepen your understanding of educational theory or seeking practical tools to support student achievement, this book provides a compelling blend of research, real-life examples, and actionable strategies. Join a movement to revolutionise education by harnessing the power of NLP—empowering students to reach their full potential and creating more engaging, effective learning environments. Perfect for anyone passionate about making a positive difference in education today!
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Mastering Python for Networking and Security
Tackle security and networking issues using Python libraries such as Nmap, requests, asyncio, and scapyKey FeaturesEnhance your Python programming skills in securing systems and executing networking tasksExplore Python scripts to debug and secure complex networksLearn to avoid common cyber events with modern Python scriptingBook DescriptionIt's now more apparent than ever that security is a critical aspect of IT infrastructure, and that devastating data breaches can occur from simple network line hacks. As shown in this book, combining the latest version of Python with an increased focus on network security can help you to level up your defenses against cyber attacks and cyber threats. Python is being used for increasingly advanced tasks, with the latest update introducing new libraries and packages featured in the Python 3.7.4 recommended version. Moreover, most scripts are compatible with the latest versions of Python and can also be executed in a virtual environment. This book will guide you through using these updated packages to build a secure network with the help of Python scripting. You'll cover a range of topics, from building a network to the procedures you need to follow to secure it. Starting by exploring different packages and libraries, you'll learn about various ways to build a network and connect with the Tor network through Python scripting. You will also learn how to assess a network's vulnerabilities using Python security scripting. Later, you'll learn how to achieve endpoint protection by leveraging Python packages, along with writing forensic scripts. By the end of this Python book, you'll be able to use Python to build secure apps using cryptography and steganography techniques.What you will learnCreate scripts in Python to automate security and pentesting tasksExplore Python programming tools that are used in network security processesAutomate tasks such as analyzing and extracting information from serversUnderstand how to detect server vulnerabilities and analyze security modulesDiscover ways to connect to and get information from the Tor networkFocus on how to extract information with Python forensics toolsWho this book is forThis Python network security book is for network engineers, system administrators, or any security professional looking to overcome networking and security challenges. You will also find this book useful if you're a programmer with prior experience in Python. A basic understanding of general programming structures and the Python programming language is required before getting started.
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Mastering Reinforcement Learning with Python
Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry problems with the help of expert tips and best practicesKey FeaturesUnderstand how large-scale state-of-the-art RL algorithms and approaches workApply RL to solve complex problems in marketing, robotics, supply chain, finance, cybersecurity, and moreExplore tips and best practices from experts that will enable you to overcome real-world RL challengesBook DescriptionReinforcement learning (RL) is a field of artificial intelligence (AI) used for creating self-learning autonomous agents. Building on a strong theoretical foundation, this book takes a practical approach and uses examples inspired by real-world industry problems to teach you about state-of-the-art RL. Starting with bandit problems, Markov decision processes, and dynamic programming, the book provides an in-depth review of the classical RL techniques, such as Monte Carlo methods and temporal-difference learning. After that, you will learn about deep Q-learning, policy gradient algorithms, actor-critic methods, model-based methods, and multi-agent reinforcement learning. Then, you'll be introduced to some of the key approaches behind the most successful RL implementations, such as domain randomization and curiosity-driven learning. As you advance, you’ll explore many novel algorithms with advanced implementations using modern Python libraries such as TensorFlow and Ray’s RLlib package. You’ll also find out how to implement RL in areas such as robotics, supply chain management, marketing, finance, smart cities, and cybersecurity while assessing the trade-offs between different approaches and avoiding common pitfalls. By the end of this book, you’ll have mastered how to train and deploy your own RL agents for solving RL problems.What you will learnModel and solve complex sequential decision-making problems using RLDevelop a solid understanding of how state-of-the-art RL methods workUse Python and TensorFlow to code RL algorithms from scratchParallelize and scale up your RL implementations using Ray's RLlib packageGet in-depth knowledge of a wide variety of RL topicsUnderstand the trade-offs between different RL approachesDiscover and address the challenges of implementing RL in the real worldWho this book is forThis book is for expert machine learning practitioners and researchers looking to focus on hands-on reinforcement learning with Python by implementing advanced deep reinforcement learning concepts in real-world projects. Reinforcement learning experts who want to advance their knowledge to tackle large-scale and complex sequential decision-making problems will also find this book useful. Working knowledge of Python programming and deep learning along with prior experience in reinforcement learning is required.
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