Data Analytics With Generative Ai
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Starting Data Analytics with Generative AI and Python
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
Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach
This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.
Advanced Data Analytics with AWS: Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources
Author: Joseph Conley
language: en
Publisher: Orange Education Pvt Limited
Release Date: 2024-04-17
Master the Fundamentals of Data Analytics at Scale Key Features ● Comprehensive guide to constructing data engineering workflows spanning diverse data sources ● Expert techniques for transforming and visualizing data to extract actionable insights ● Advanced methodologies for analyzing data and employing machine learning to uncover intricate patterns Book Description Embark on a transformative journey into the realm of data analytics with AWS with this practical and incisive handbook. Begin your exploration with an insightful introduction to the fundamentals of data analytics, setting the stage for your AWS adventure. The book then covers collecting data efficiently and effectively on AWS, laying the groundwork for insightful analysis. It will dive deep into processing data, uncovering invaluable techniques to harness the full potential of your datasets. The book will equip you with advanced data analysis skills, unlocking the ability to discern complex patterns and insights. It covers additional use cases for data analysis on AWS, from predictive modeling to sentiment analysis, expanding your analytical horizons. The final section of the book will utilize the power of data virtualization and interaction, revolutionizing the way you engage with and derive value from your data. Gain valuable insights into emerging trends and technologies shaping the future of data analytics, and conclude your journey with actionable next steps, empowering you to continue your data analytics odyssey with confidence. What you will learn ● Construct streamlined data engineering workflows capable of ingesting data from diverse sources and formats. ● Employ data transformation tools to efficiently cleanse and reshape data, priming it for analysis. ● Perform ad-hoc queries for preliminary data exploration, uncovering initial insights. ● Utilize prepared datasets to craft compelling, interactive data visualizations that communicate actionable insights. ● Develop advanced machine learning and Generative AI workflows to delve into intricate aspects of complex datasets, uncovering deeper insights. Table of Contents 1. Introduction to Data Analytics and AWS 2. Getting Started with AWS 3. Collecting Data with AWS 4. Processing Data on AWS 5. Descriptive Analytics on AWS 6. Advanced Data Analysis on AWS 7. Additional Use Cases for Data Analysis 8. Data Visualization and Interaction on AWS 9. The Future of Data Analytics 10. Conclusion and Next Steps Index