Dive Into Data Science

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Dive Into Data Science

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Author : Bradford Tuckfield
language : en
Publisher: No Starch Press
Release Date : 2023-07-04

Dive Into Data Science written by Bradford Tuckfield and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-04 with Computers categories.

Learn how to use data science and Python to solve everyday business problems. Dive into the exciting world of data science with this practical introduction. Packed with essential skills and useful examples, Dive Into Data Science will show you how to obtain, analyze, and visualize data so you can leverage its power to solve common business challenges. With only a basic understanding of Python and high school math, you’ll be able to effortlessly work through the book and start implementing data science in your day-to-day work. From improving a bike sharing company to extracting data from websites and creating recommendation systems, you’ll discover how to find and use data-driven solutions to make business decisions. Topics covered include conducting exploratory data analysis, running A/B tests, performing binary classification using logistic regression models, and using machine learning algorithms. You’ll also learn how to: Forecast consumer demand Optimize marketing campaigns Reduce customer attrition Predict website traffic Build recommendation systems With this practical guide at your fingertips, harness the power of programming, mathematical theory, and good old common sense to find data-driven solutions that make a difference. Don’t wait; dive right in!

A Beginner S Guide To Data Science

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Author : Enamul Haque
language : en
Publisher:
Release Date : 2023-01-06

A Beginner S Guide To Data Science written by Enamul Haque and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-06 with categories.

This book is designed for aspiring data scientists who want to start their careers in data science, even if they don't have coding skills. It provides a comprehensive introduction to the foundations of data science and its applications, using simple language that is easy for beginners to understand. No technical expertise is required to master the material in this book. It is an ideal resource for anyone looking to learn about data science in an accessible and straightforward way. Key features include: Introduction to data science History of data science Data science life-cycle Data science tools and technologies Data science methodology Data science models Developing data science business strategy Managing data science projects Becoming a data scientist, data engineer etc. Big data Data Mining Artificial intelligence Machine learning Deep learning Neural networks Mathematical analysis Statistical modelling Understanding the fundamentals of data science programming languages Database structures and principles Robotic Process Automation Data science acronyms You need to know And a lot more.

A Beginners Guide To Data Science

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Author : Enamul Haque
language : en
Publisher:
Release Date : 2021-03-31

A Beginners Guide To Data Science written by Enamul Haque and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-31 with categories.

Calling all the Aspiring Data Scientists! This book is your "one-stop-shop" to kick start your data science career without knowing how to code! In fact, data science doesn't have to be complicated! With this book, you will grow an understanding of the foundations of data science and its applications. To master this book, you don't need technical abilities. This book is recommended for beginners and anybody who want to understand data science conveniently. You don't need a big textbook to master data science today. A straightforward language has been used to ensure ease of understanding, especially for beginners. Key features include: Introduction to data scienceHistory of data scienceData science life-cycleData science tools and technologiesData science methodologyData science modelsDeveloping data science business strategyManaging data science projectsBecoming a data scientist, data engineers etc.Doing data science without codingBig dataData MiningArtificial intelligenceMachine learningDeep learningNeural networksMathematical analysisStatistical modellingUnderstanding the fundamentals of Python and RDatabase structures and principlesRobotic Process AutomationData science acronyms you need to knowOnline free data science learning resources And a lot more

Leading With Ai And Analytics Build Your Data Science Iq To Drive Business Value

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Author : Eric Anderson
language : en
Publisher: McGraw Hill Professional
Release Date : 2020-11-23

Leading With Ai And Analytics Build Your Data Science Iq To Drive Business Value written by Eric Anderson and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-23 with Business & Economics categories.

Lead your organization to become evidence-driven Data. It’s the benchmark that informs corporate projections, decision-making, and analysis. But, why do many organizations that see themselves as data-driven fail to thrive? In Leading with AI and Analytics, two renowned experts from the Kellogg School of Management show business leaders how to transform their organization to become evidence-driven, which leads to real, measurable changes that can help propel their companies to the top of their industries. The availability of unprecedented technology-enabled tools has made AI (Artificial Intelligence) an essential component of business analytics. But what’s often lacking are the leadership skills to integrate these technologies to achieve maximum value. Here, the authors provide a comprehensive game plan for developing that all-important human factor to get at the heart of data science: the ability to apply analytical thinking to real-world problems. Each of these tools and techniques comes to powerful life through a wealth of powerful case studies and real-world success stories. Inside, you’ll find the essential tools to help you: Develop a strong data science intuition quotient Lead and scale AI and analytics throughout your organization Move from “best-guess” decision making to evidence-based decisions Craft strategies and tactics to create real impact Written for anyone in a leadership or management role—from C-level/unit team managers to rising talent—this powerful, hands-on guide meets today’s growing need for real-world tools to lead and succeed with data.

Data Science From Scratch

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Author : Joel Grus
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-04-12

Data Science From Scratch written by Joel Grus 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 2019-04-12 with Computers categories.

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. With this updated second edition, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.

Python

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Author : Steve Geddis
language : en
Publisher:
Release Date : 2020-10-08

Python written by Steve Geddis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-08 with categories.

Why should you start learning Python? Is Python the only way to go if you are interested in programming? Python programming has become a must-learn skill in the Data Science domain. It has evolved as the most preferred programming language for data-driven development because it is suitable for many data science tasks and is easy to learn compared to other programming languages. In short, Python is the closest programming language to fit the goal of a beginner and a great starting place. However, Python is not the silver bullet for all problems. It certainly fits good for many purposes but it less fits for others. Being a good programmer means knowing that no single language can tackle every task. That is why knowing what kinds of advantages different programming languages can provide is certainly a good knowledge to have. This bundle aims to help by guiding you through the potentials of Python and giving you an overview of other recommended coding languages in use today so that you can pick the one that best fits your use case. Included in this bundle are: 1) Data Science from Scratch with Python The Python programming environment; Basics of data analysis in Python; What is a Data Scientist? Functionality and features used for data science; Data manipulation using the Python Pandas; Models such as neural networks, plotting and clustering; 2) Python Programming for Beginners The reasons why it is important to study coding today; The features that make Python such a powerful language; The fundamentals and techniques of Python and other most common coding languages (such as Java, PHP, C++), the best practices that coders and developers abide by when coming up with codes. Take your programming language skills to the next level, buy this book and get started!

Business Data Science Combining Machine Learning And Economics To Optimize Automate And Accelerate Business Decisions

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Author : Matt Taddy
language : en
Publisher: McGraw Hill Professional
Release Date : 2019-08-23

Business Data Science Combining Machine Learning And Economics To Optimize Automate And Accelerate Business Decisions written by Matt Taddy and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-23 with Business & Economics categories.

Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.

Natural Language Processing In Action Second Edition

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Author : Hobson Lane
language : en
Publisher: Simon and Schuster
Release Date : 2025-02-25

Natural Language Processing In Action Second Edition written by Hobson Lane 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 2025-02-25 with Computers categories.

Develop your NLP skills from scratch, with an open source toolbox of Python packages, Transformers, Hugging Face, vector databases, and your own Large Language Models. Natural Language Processing in Action, Second Edition has helped thousands of data scientists build machines that understand human language. In this new and revised edition, you’ll discover state-of-the art Natural Language Processing (NLP) models like BERT and HuggingFace transformers, popular open-source frameworks for chatbots, and more. You’ll create NLP tools that can detect fake news, filter spam, deliver exceptional search results and even build truthfulness and reasoning into Large Language Models (LLMs). In Natural Language Processing in Action, Second Edition you will learn how to: • Process, analyze, understand, and generate natural language text • Build production-quality NLP pipelines with spaCy • Build neural networks for NLP using Pytorch • BERT and GPT transformers for English composition, writing code, and even organizing your thoughts • Create chatbots and other conversational AI agents In this new and revised edition, you’ll discover state-of-the art NLP models like BERT and HuggingFace transformers, popular open-source frameworks for chatbots, and more. Plus, you’ll discover vital skills and techniques for optimizing LLMs including conversational design, and automating the “trial and error” of LLM interactions for effective and accurate results. About the technology From nearly human chatbots to ultra-personalized business reports to AI-generated email, news stories, and novels, natural language processing (NLP) has never been more powerful! Groundbreaking advances in deep learning have made high-quality open source models and powerful NLP tools like spaCy and PyTorch widely available and ready for production applications. This book is your entrance ticket—and backstage pass—into the next generation of natural language processing. About the book Natural Language Processing in Action, Second Edition introduces the foundational technologies and state-of-the-art tools you’ll need to write and publish NLP applications. You learn how to create custom models for search, translation, writing assistants, and more, without relying on big commercial foundation models. This fully updated second edition includes coverage of BERT, Hugging Face transformers, fine-tuning large language models, and more. What's inside • NLP pipelines with spaCy • Neural networks with PyTorch • BERT and GPT transformers • Conversational design for chatbots About the reader For intermediate Python programmers familiar with deep learning basics. About the author Hobson Lane is a data scientist and machine learning engineer with over twenty years of experience building autonomous systems and NLP pipelines. Maria Dyshel is a social entrepreneur and artificial intelligence expert, and the CEO and cofounder of Tangible AI. Cole Howard and Hannes Max Hapke were co-authors of the first edition.

Master Data Analysis With Python

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Author : Teddy Petrou
language : en
Publisher: No Starch Press
Release Date : 2024-11-12

Master Data Analysis With Python written by Teddy Petrou and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-12 with Computers categories.

This comprehensive but easy-to-follow deep dive into data analysis and visualization in the Python programming language is packed with practical examples and exercises that use real-world datasets. This book is an in-depth guide to best practices for data analysis and visualization in Python. It focuses on various Python libraries, showing you how to optimize their performance with the most up-to-date syntax. After learning the basics of the pandas library, you’ll dive into how to use it for conducting nearly any kind of data analysis—complete with exercises in every chapter that test your newfound skills on real-world datasets, like tracking Chicago bikers. You’ll also explore the matplotlib and seaborn libraries, and try out some of the most common tasks during data analysis, including selecting subsets of the data and performing calculations on single or multiple columns. Learn to: Apply operations to independent groups within a dataset Observe data over a period of time Tidy your data and display it in a reader-friendly way Join multiple datasets to work with them at the same time Set up a robust environment on your system to do data science Master Data Analysis with Python is a masterclass in the best practices, libraries, and techniques for collecting, analyzing, and visualizing data with the world’s most popular, easy-to-learn language.

Diving For Science 1998

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Author :
language : en
Publisher:
Release Date : 1998

Diving For Science 1998 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Deep diving categories.