Starting Data Analytics With Generative Ai And Python

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Starting Data Analytics With Generative Ai And Python

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Author : Artur Guja
language : en
Publisher: Simon and Schuster
Release Date : 2024-12-24

Starting Data Analytics With Generative Ai And Python written by Artur Guja 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 2024-12-24 with Computers categories.

Accelerate your mastery of data analytics with the power of ChatGPT. Whether you’re brand new to data analysis or an experienced pro looking to do more work, faster, Starting Data Analytics with Generative AI and Python is here to help simplify and speed up your data analysis! Written by a pair of world-class data scientists and an experienced risk manager, the book concentrates on the practical analytics tasks you'll do every day. Inside Starting Data Analytics with Generative AI and Python you’ll learn how to: • Write great prompts for ChatGPT • Perform end-to-end descriptive analytics • Set up an AI-friendly data analytics environment • Evaluate the quality of your data • Develop a strategic analysis plan • Generate code to analyze non-text data • Explore text data directly with ChatGPT • Prepare reliable reports In Starting Data Analytics with Generative AI and Python you’ll learn how to improve your coding efficiency, generate new analytical approaches, and fine-tune data pipelines—all assisted by AI tools like ChatGPT. For each step in the data process, you’ll discover how ChatGPT can implement data techniques from simple plain-English prompts. Plus, you’ll develop a vital intuition about the risks and errors that still come with these tools. About the technology If you have basic knowledge of data analysis, this book will show you how to use ChatGPT to accelerate your essential data analytics work. This speed-up can be amazing: the authors report needing one third or even one quarter the time they needed before. About the book You’ll find reliable and practical advice that works on the job. Improve problem exploration, generate new analytical approaches, and fine-tune your data pipelines—all while developing an intuition about the risks and errors that still come with AI tools. In the end, you’ll be able to do significantly more work, do it faster, and get better results, without breaking a sweat. Assuming only that you know the foundations, this friendly book guides you through the entire analysis process—from gathering and preparing raw data, data cleaning, generating code-based solutions, selecting statistical tools, and finally creating effective data presentations. With clearly-explained prompts to extract, interpret, and present data, it will raise your skills to a whole different level. What's inside • Write great prompts for ChatGPT • Perform end-to-end descriptive analytics • Set up an AI-friendly data analytics environment • Evaluate the quality of your data • Develop a strategic analysis plan • Generate code to analyze non-text data • Explore text data directly with ChatGPT • Prepare reliable reports About the author Authors Artur Guja, Dr. Marlena Siwiak, and Dr. Marian Siwiak are experienced data scientists with backgrounds in business, scientific research, and finance. The technical editor on this book was Mike Jensen. Table of Contents 1 Introduction to the use of generative AI in data analytics 2 Using generative AI to ensure sufficient data quality 3 Descriptive analysis and statistical inference supported by generative AI 4 Using generative AI for result interpretations 5 Basic text mining using generative AI 6 Advanced text mining with generative AI 7 Scaling and performance optimization 8 Risk, mitigation, and tradeoffs Appendix A Specifying multiple DataFrames to ChatGPT v4 Appendix B On debugging ChatGPT’s code Appendix C On laziness and human errors

Social Data Analytics In The Cloud With Ai

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Author : Xuebin Wei
language : en
Publisher: CRC Press
Release Date : 2024-12-30

Social Data Analytics In The Cloud With Ai written by Xuebin Wei and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Technology & Engineering categories.

The rise of cloud computing and Generative artificial intelligence (AI) has revolutionized data analytics pipelines. Analysts can collect, store, and process vast datasets in the cloud with high availability and scalability, and also leverage Generative AI to query and visualize datasets in natural languages. This pioneering textbook provides a gateway for students, educators, and professionals to develop and enhance social data analytics capabilities with the latest cloud computing and AI technologies. The textbook introduces educational cloud resources from leading technology companies, begins with foundational concepts, and progresses to advanced techniques. Features The first textbook on cloud-based social data analytics with the assistance of Generative AI. Introduces educational cloud resources from leading technology companies like AWS, GitHub, and MongoDB. Presents a fully AI-powered data analytics pipeline from Python coding to data collection with APIs, cloud-based data storage, natural language queries, and interactive visualization. Analyzes Census and social media data with the latest large language models (LLMs). Provides hands-on exercises with real-world datasets on timely issues. This textbook is an excellent resource for upper-level undergraduate and graduate students taking GIS, Urban Informatics, Social Science Data Analysis, and Data Science courses; faculty members teaching such courses; and professionals and researchers interested in leveraging cloud computing and Generative AI in social data analytics.

Data Analytics With Generative Ai

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Author :
language : en
Publisher:
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Data Analytics With Generative Ai written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.

How To Become A Prompt Engineer A Comprehensive Guide To Start Your Prompt Engineer Career

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Author : Bernhard Gaum
language : en
Publisher: Bernhard Gaum
Release Date : 2024-11-11

How To Become A Prompt Engineer A Comprehensive Guide To Start Your Prompt Engineer Career written by Bernhard Gaum and has been published by Bernhard Gaum this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-11 with Business & Economics categories.

Unlock the secrets to mastering AI communication with *How to Become a Prompt Engineer*. As artificial intelligence continues to shape our world, the ability to craft effective prompts has become an essential skill for anyone looking to harness the full potential of AI systems. This guide provides a comprehensive introduction to the art and science of prompt engineering, empowering you to create clear, relevant, and powerful AI interactions. Through practical techniques, real-world examples, and hands-on activities, you'll learn how to design prompts that yield accurate and meaningful responses. From avoiding common pitfalls to refining prompts through iteration, each chapter equips you with the tools and strategies to improve AI outputs and navigate complex AI applications. Whether you're a tech enthusiast, content creator, developer, or just curious about AI, *How to Become a Prompt Engineer* will help you master the skills needed to succeed in the fast-evolving world of AI and natural language processing. Start your journey today and discover how to transform simple queries into sophisticated AI-driven solutions!

Artificial Intelligence With Python

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Author : Prateek Joshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-01-27

Artificial Intelligence With Python written by Prateek Joshi 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 2017-01-27 with Computers categories.

Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.

Python Simplified With Generative Ai

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Author : Duc T. Haba
language : en
Publisher: BPB Publications
Release Date : 2025-04-25

Python Simplified With Generative Ai written by Duc T. Haba and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-25 with Computers categories.

DESCRIPTION GenAI and Python are changing how we use technology, making it essential to understand both to stay innovative and work efficiently. GenAI significantly impacts learning Python by generating personalized code snippets, accelerating the learning process. This book bridges the gap between traditional education and the practical challenges students encounter today. It combines hands-on learning with modern GenAI tools like GPT-4 and Copilot. The book begins with fundamental GenAI concepts, including GPT-4 and Gemini, and mastering prompt engineering for optimal GenAI interaction. Instead of starting with technical details like algorithms and syntax, it introduces coding through interactive, practical Python Jupyter Notebooks and Google Colab projects. Readers will learn Python code with a calculator application, explore fundamental sorting algorithms, and manipulate data using Pandas. The book then explores advanced ML through CNN image classification with Fast.ai, and deploying AI models as web applications using Hugging Face and Gradio. It also addresses critical ethical considerations in AI, focusing on fairness and bias, and provides career guidance for modern programmers. Moreover, this book takes a fresh approach to learning by prioritizing exploration and creativity, much like the way Gen Z engage with games, apps, and hands-on activities. By the end of this book, you will be equipped with the practical skills and ethical understanding to confidently apply Python and GenAI in diverse projects, helping you navigate the evolving landscape of AI-driven development. WHAT YOU WILL LEARN ● Write and debug Python code through hands-on projects. ● Learn GenAI setup, and effective prompt engineering. ● Step-by-step Python projects using Jupyter Notebooks and GenAI. ● Deploy AI models as interactive web applications using Hugging Face and Gradio frameworks. ● Leverage GenAI tools like GPT-4 and Copilot. ● Understand AI bias and use it responsibly for positive impact. WHO THIS BOOK IS FOR This book is for professionals interested in learning Python and using GenAI tools like GPT-4 in practical applications. It is for aspiring programmers, students, and data analysts seeking practical Python and GenAI skills. TABLE OF CONTENTS 1. Introduction to GenAI 2. Jupyter Notebook 3. Dissect The Calculator App 4. Sorting on My Mind 5. Pandas, the Data Tamer 6. Decipher CNN App 7. Gradio and Hugging Face Deployment 8. Fairness and Bias 9. Your Turn to Be a Code Walker

Data Science And Analytics With Python

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Author : Jesus Rogel-Salazar
language : en
Publisher: CRC Press
Release Date : 2025-06-03

Data Science And Analytics With Python written by Jesus Rogel-Salazar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-03 with Computers categories.

Since the first edition of “Data Science and Analytics with Python” we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI). This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucial issues of explainability, transparency, and fairness in AI. These topics have rightly gained significant attention in recent years. As AI integrates more deeply into various aspects of our lives, understanding and mitigating biases, ensuring fairness, and maintaining transparency become paramount. This book provides comprehensive coverage of these topics, offering practical insights and guidance for data scientists and analysts. Designed as a practical companion for data analysts and budding data scientists, this book assumes a working knowledge of programming and statistical modelling but aims to guide readers deeper into the wonders of data analytics and machine learning. Maintaining the book's structure, each chapter stands alone as much as possible, allowing readers to use it as a reference as well as a textbook. Whether revisiting fundamental concepts or diving into new, advanced topics, this book offers something valuable for every reader.

Python For Data Analysis

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Author : Wes McKinney
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-09-25

Python For Data Analysis written by Wes McKinney 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 2017-09-25 with Computers categories.

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples

Data Labeling In Machine Learning With Python

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Author : Vijaya Kumar Suda
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-01-31

Data Labeling In Machine Learning With Python written by Vijaya Kumar Suda 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 2024-01-31 with Computers categories.

Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labeling Key Features Generate labels for regression in scenarios with limited training data Apply generative AI and large language models (LLMs) to explore and label text data Leverage Python libraries for image, video, and audio data analysis and data labeling Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today’s data-driven world, mastering data labeling is not just an advantage, it’s a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you’ll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.What you will learn Excel in exploratory data analysis (EDA) for tabular, text, audio, video, and image data Understand how to use Python libraries to apply rules to label raw data Discover data augmentation techniques for adding classification labels Leverage K-means clustering to classify unsupervised data Explore how hybrid supervised learning is applied to add labels for classification Master text data classification with generative AI Detect objects and classify images with OpenCV and YOLO Uncover a range of techniques and resources for data annotation Who this book is for This book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.

Modern Data Analytics In Excel

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Author : George Mount
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-04-26

Modern Data Analytics In Excel written by George Mount 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 2024-04-26 with Computers categories.

If you haven't modernized your data cleaning and reporting processes in Microsoft Excel, you're missing out on big productivity gains. And if you're looking to conduct rigorous data analysis, more can be done in Excel than you think. This practical book serves as an introduction to the modern Excel suite of features along with other powerful tools for analytics. George Mount of Stringfest Analytics shows business analysts, data analysts, and business intelligence specialists how to make bigger gains right from your spreadsheets by using Excel's latest features. You'll learn how to build repeatable data cleaning workflows with Power Query, and design relational data models straight from your workbook with Power Pivot. You'll also explore other exciting new features for analytics, such as dynamic array functions, AI-powered insights, and Python integration. Learn how to build reports and analyses that were previously difficult or impossible to do in Excel. This book shows you how to: Build repeatable data cleaning processes for Excel with Power Query Create relational data models and analysis measures with Power Pivot Pull data quickly with dynamic arrays Use AI to uncover patterns and trends from inside Excel Integrate Python functionality with Excel for automated analysis and reporting