Training Your Systems With Python Statistical Modeling
DOWNLOAD
Download Training Your Systems With Python Statistical Modeling PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Training Your Systems With Python Statistical Modeling 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
Training Systems Using Python Statistical Modeling
DOWNLOAD
Author : Curtis Miller
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-20
Training Systems Using Python Statistical Modeling written by Curtis Miller 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 2019-05-20 with Computers categories.
Leverage the power of Python and statistical modeling techniques for building accurate predictive models Key FeaturesGet introduced to Python's rich suite of libraries for statistical modelingImplement regression, clustering and train neural networks from scratchIncludes real-world examples on training end-to-end machine learning systems in PythonBook Description Python's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today. Its rich libraries are widely used for data analysis, and more importantly, for building state-of-the-art predictive models. This book takes you through an exciting journey, of using these libraries to implement effective statistical models for predictive analytics. You’ll start by diving into classical statistical analysis, where you will learn to compute descriptive statistics using pandas. You will look at supervised learning, where you will explore the principles of machine learning and train different machine learning models from scratch. You will also work with binary prediction models, such as data classification using k-nearest neighbors, decision trees, and random forests. This book also covers algorithms for regression analysis, such as ridge and lasso regression, and their implementation in Python. You will also learn how neural networks can be trained and deployed for more accurate predictions, and which Python libraries can be used to implement them. By the end of this book, you will have all the knowledge you need to design, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive analytics. What you will learnUnderstand the importance of statistical modelingLearn about the various Python packages for statistical analysisImplement algorithms such as Naive Bayes, random forests, and moreBuild predictive models from scratch using Python's scikit-learn libraryImplement regression analysis and clusteringLearn how to train a neural network in PythonWho this book is for If you are a data scientist, a statistician or a machine learning developer looking to train and deploy effective machine learning models using popular statistical techniques, then this book is for you. Knowledge of Python programming is required to get the most out of this book.
Training Your Systems With Python Statistical Modeling
DOWNLOAD
Author : Curtis Miller
language : en
Publisher:
Release Date : 2018
Training Your Systems With Python Statistical Modeling written by Curtis Miller and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
"Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. This course takes you through the various different concepts that get you acquainted and working with the different aspects of Machine Learning. You'll start by diving into classical statistical analysis, where you will learn to compute descriptive statistics with Pandas. From there, you will be introduced to supervised learning, where you will explore the principles of machine learning and train different machine learning models. Next, you'll work with binary prediction models, such as data classification using K-nearest neighbors, decision trees, and random forests. After that, you'll work with algorithms for regression analysis, and employ different types of regression, such as ridge and lasso regression, and spline interpolation using SciPy. Then, you'll work on neural networks, train them, and employ regression on neural networks. You'll be introduced to clustering, and learn to evaluate cluster model results, as well as employ different clustering types such as hierarchical and spectral clustering. Finally, you'll learn about the dimensionality reduction concepts such as principal component analysis and low dimension representation."--Resource description page.
Mastering Spacy
DOWNLOAD
Author : Déborah Mesquita
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-02-14
Mastering Spacy written by Déborah Mesquita 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 2025-02-14 with Computers categories.
Discover how to master advanced spaCy techniques, including custom pipelines, LLM integration, and model training, to build NLP solutions efficiently and effectively Key Features Build End-to-End NLP Workflows, From Local Development to Production with Weasel and FastAPI Master No-Training NLP Development with spaCy-LLM, From Prompt Engineering to Custom Tasks Create Advanced NLP Solutions, From Custom Components to Neural Coreference Resolution Book Description Mastering spaCy, Second Edition is your comprehensive guide to building sophisticated NLP applications using the spaCy ecosystem. This revised edition embraces the latest advancements in NLP, featuring new chapters on Large Language Models with spaCy-LLM, transformers integration, and end-to-end workflow management with Weasel. With this new edition you’ll learn to enhance NLP tasks using LLMs with spaCy-llm, manage end-to-end workflows using Weasel and integrating spaCy with third-party libraries like Streamlit, FastAPI, and DVC. From training custom named entity recognition (NER) pipelines to categorizing emotions in Reddit posts, readers will explore advanced topics like text classification and coreference resolution. This book takes you on a journey through spaCy’s capabilities, starting with the fundamentals of NLP, such as tokenization, named entity recognition, and dependency parsing. As you progress, you’ll delve into advanced topics like creating custom components, training domain-specific models, and building scalable NLP workflows. By end of the book, through practical examples, clear explanations, tips and tricks you will be empowered to build robust NLP pipelines and integrate them with web applications to build end-to-end solutions. What will you learn Apply transformer models and fine-tune them for specialized NLP tasks Master spaCy core functionalities including data structures and processing pipelines Develop custom pipeline components and semantic extractors for domain-specific needs Build scalable applications by integrating spaCy with FastAPI, Streamlit, and DVC Master advanced spaCy features including coreference resolution and neural pipeline components Train domain-specific models, including NER and coreference resolution Prototype rapidly with spaCy-LLM and develop custom LLM tasks Who this book is for This book is tailored for NLP engineers, machine learning developers, and LLM engineers looking to build production-grade language processing solutions. While primarily targeting professionals working with language models and NLP pipelines, it's also valuable for software engineers transitioning into NLP development. Basic Python programming knowledge and familiarity with NLP concepts is recommended to leverage spaCy's latest capabilities.
The Influxdb Handbook
DOWNLOAD
Author : Robert Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-02-01
The Influxdb Handbook written by Robert Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-01 with Computers categories.
This handbook serves as a definitive guide to InfluxDB, detailing its architecture, configuration, and optimization for managing time series data. It covers foundational concepts, advanced query techniques, data modeling strategies, and practical approaches for deploying secure, high-performing systems. Each chapter is crafted to build a comprehensive understanding of InfluxDB’s capabilities, facilitating efficient data analysis and system scaling. The content is presented in a clear, matter-of-fact style tailored for professionals seeking to enhance their technical expertise. With real-world case studies and practical advice, this book equips readers with the necessary tools to deploy, monitor, and troubleshoot InfluxDB in diverse operational environments.
The Llm Guide Extended Edition
DOWNLOAD
Author : shivam kumar
language : en
Publisher: visionquantech
Release Date : 2025-10-24
The Llm Guide Extended Edition written by shivam kumar and has been published by visionquantech this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-24 with Antiques & Collectibles categories.
Technical guide for AI enthusiasts and developers on creating and fine-tuning LLMs like ChatGPT and Claude.
Artificial Intelligence
DOWNLOAD
Author : Prabhu TL
language : en
Publisher: NestFame Creations Pvt Ltd.
Release Date : 2025-04-05
Artificial Intelligence written by Prabhu TL and has been published by NestFame Creations Pvt Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-05 with Computers categories.
Artificial Intelligence From Fundamentals to the Future – Master the World of Thinking Machines Unlock the secrets behind the most transformative technology of our time. Whether you’re a student, tech enthusiast, entrepreneur, or simply curious about the future, Artificial Intelligence is your ultimate guide to understanding, building, and ethically navigating intelligent systems. This comprehensive, easy-to-follow book takes you on a powerful journey through the core principles, tools, applications, and philosophical challenges of AI—from the basics to the bleeding edge. 🔍 Inside this book, you will discover: ✅ What AI really is—and how it differs from human intelligence ✅ The history, evolution, and types of AI (Narrow, General, and Super Intelligence) ✅ Foundations of machine learning, deep learning, NLP, and computer vision ✅ Real-world AI applications in healthcare, finance, education, marketing, and more ✅ How to build your own AI models with hands-on examples ✅ Emerging technologies: quantum AI, emotional intelligence, and AGI ✅ Ethics, bias, consciousness, and the role of AI in reshaping humanity 👩💻 Who is this book for? Students & professionals looking to upskill in AI Entrepreneurs & product creators wanting to leverage AI Academics & researchers exploring the cutting edge Policy makers & thinkers interested in ethical implications Anyone curious about how AI is shaping our present—and future 🌍 More than a book—it’s a roadmap for the intelligent age. In a world increasingly shaped by algorithms, this book empowers you to not just understand AI—but to use it wisely, build it responsibly, and shape its future with intention and impact. Start your journey today. The future isn’t just coming— AI is already here. Are you ready?
Hands On Data Analysis With Numpy And Pandas
DOWNLOAD
Author : Curtis Miller
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-29
Hands On Data Analysis With Numpy And Pandas written by Curtis Miller 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 2018-06-29 with Computers categories.
Get to grips with the most popular Python packages that make data analysis possible Key Features Explore the tools you need to become a data analyst Discover practical examples to help you grasp data processing concepts Walk through hierarchical indexing and grouping for data analysis Book Description Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation. What you will learn Understand how to install and manage Anaconda Read, sort, and map data using NumPy and pandas Find out how to create and slice data arrays using NumPy Discover how to subset your DataFrames using pandas Handle missing data in a pandas DataFrame Explore hierarchical indexing and plotting with pandas Who this book is for Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book.
Solutions Architect S Handbook
DOWNLOAD
Author : Saurabh Shrivastava
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-01-17
Solutions Architect S Handbook written by Saurabh Shrivastava 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 2022-01-17 with Computers categories.
Third edition out now with coverage on Generative AI, clean architecture, edge computing, and more Key Features Turn business needs into end-to-end technical architectures with this practical guide Assess and overcome various challenges while updating or modernizing legacy applications Future-proof your architecture with IoT, machine learning, and quantum computing Book DescriptionBecoming a solutions architect requires a hands-on approach, and this edition of the Solutions Architect's Handbook brings exactly that. This handbook will teach you how to create robust, scalable, and fault-tolerant solutions and next-generation architecture designs in a cloud environment. It will also help you build effective product strategies for your business and implement them from start to finish. This new edition features additional chapters on disruptive technologies, such as Internet of Things (IoT), quantum computing, data engineering, and machine learning. It also includes updated discussions on cloud-native architecture, blockchain data storage, and mainframe modernization with public cloud. The Solutions Architect's Handbook provides an understanding of solution architecture and how it fits into an agile enterprise environment. It will take you through the journey of solution architecture design by providing detailed knowledge of design pillars, advanced design patterns, anti-patterns, and the cloud-native aspects of modern software design. By the end of this handbook, you'll have learned the techniques needed to create efficient architecture designs that meet your business requirements.What you will learn Explore the various roles of a solutions architect in the enterprise landscape Implement key design principles and patterns to build high-performance cost-effective solutions Choose the best strategies to secure your architectures and increase their availability Modernize legacy applications with the help of cloud integration Understand how big data processing, machine learning, and IoT fit into modern architecture Integrate a DevOps mindset to promote collaboration, increase operational efficiency, and streamline production Who this book is for This book is for software developers, system engineers, DevOps engineers, architects, and team leaders who already work in the IT industry and aspire to become solutions architect professionals. Existing solutions architects who want to expand their skillset or get a better understanding of new technologies will also learn valuable new skills. To get started, you'll need a good understanding of the real-world software development process and general programming experience in any language.
Azure Ai Engineer Associate Ai 102 Study Guide
DOWNLOAD
Author : Renaldi Gondosubroto
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-09-09
Azure Ai Engineer Associate Ai 102 Study Guide written by Renaldi Gondosubroto and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-09 with Computers categories.
With the GenAI boom showing no sign of letup, the demand for AI skills will only increase with time and innovation. Microsoft Azure leads the pack with services for developing and deploying AI solutions, so professionals looking to break into this field should consider pursuing certification as an Azure AI Engineer Associate. Azure's AI-102 exam isn't a piece of cake, but author Renaldi Gondosubroto makes it a great deal more approachable with this comprehensive study guide. Packed with expert guidance, it covers everything you'll need to know to pass the exam. You'll dive deep into all the phases of AI solutions development, from requirements definition and design to development, deployment, and integration, along with maintenance, performance tuning, and monitoring throughout. The book also takes you through practical implementation of these systems, covering decision support, computer vision, natural language processing, knowledge mining, document intelligence, and generative AI solutions. Understand the core concepts of Azure AI services Develop and deploy AI solutions within Azure's environment Explore integration and security practices with Azure AI services Optimize and troubleshoot AI models on Azure Gain knowledge about building GenAI solutions on Azure and put it into practice
Statistics Every Programmer Needs
DOWNLOAD
Author : Gary Sutton
language : en
Publisher: Simon and Schuster
Release Date : 2025-09-09
Statistics Every Programmer Needs written by Gary Sutton and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-09 with Computers categories.
Put statistics into practice with Python! Data-driven decisions rely on statistics. Statistics Every Programmer Needs introduces the statistical and quantitative methods that will help you go beyond “gut feeling” for tasks like predicting stock prices or assessing quality control, with examples using the rich tools of the Python ecosystem. Statistics Every Programmer Needs will teach you how to: • Apply foundational and advanced statistical techniques • Build predictive models and simulations • Optimize decisions under constraints • Interpret and validate results with statistical rigor • Implement quantitative methods using Python In this hands-on guide, stats expert Gary Sutton blends the theory behind these statistical techniques with practical Python-based applications, offering structured, reproducible, and defensible methods for tackling complex decisions. Well-annotated and reusable Python code listings illustrate each method, with examples you can follow to practice your new skills. About the technology Whether you’re analyzing application performance metrics, creating relevant dashboards and reports, or immersing yourself in a numbers-heavy coding project, every programmer needs to know how to turn raw data into actionable insight. Statistics and quantitative analysis are the essential tools every programmer needs to clarify uncertainty, optimize outcomes, and make informed choices. About the book Statistics Every Programmer Needs teaches you how to apply statistics to the everyday problems you’ll face as a software developer. Each chapter is a new tutorial. You’ll predict ultramarathon times using linear regression, forecast stock prices with time series models, analyze system reliability using Markov chains, and much more. The book emphasizes a balance between theory and hands-on Python implementation, with annotated code and real-world examples to ensure practical understanding and adaptability across industries. What's inside • Probability basics and distributions • Random variables • Regression • Decision trees and random forests • Time series analysis • Linear programming • Monte Carlo and Markov methods and much more About the reader Examples are in Python. About the author Gary Sutton is a business intelligence and analytics leader and the author of Statistics Slam Dunk: Statistical analysis with R on real NBA data. Table of Contents 1 Laying the groundwork 2 Exploring probability and counting 3 Exploring probability distributions and conditional probabilities 4 Fitting a linear regression 5 Fitting a logistic regression 6 Fitting a decision tree and a random forest 7 Fitting time series models 8 Transforming data into decisions with linear programming 9 Running Monte Carlo simulations 10 Building and plotting a decision tree 11 Predicting future states with Markov analysis 12 Examining and testing naturally occurring number sequences 13 Managing projects 14 Visualizing quality control Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.