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Data Visualization Guide: Clear Guide to Data Science and Visualization

1 การให้คะแนน

2

ระยะเวลา
5H 23นาที
ภาษา
ภาษาอังกฤษ
Format
หมวดหมู่

นอนฟิกชั่น

Have you ever wondered how you can work with large volumes of data sets?

Do you ever think about how you can use these data sets to identify hidden patterns and make an informed decision?

Do you know where you can collect this information?

Have you ever questioned what you can do with incomplete or incorrect data sets?

If you said yes to any of these questions, then you have come to the right place.

Most businesses collect information from various sources. This information can be in different formats and needs to be collected, processed, and improved upon if you want to interpret it. You can use various data mining tools to source the information from different places. These tools can also help with the cleaning and processing techniques.

You can use this information to make informed decisions and improve the efficiency and methods in your business. Every business needs to find a way to interpret and analyze large data sets. To do this, you will need to learn more about the different libraries and functions used to improve data sets. Since most data professionals use Python as the base programming language to develop models, this book uses some common libraries and functions from Python to give you a brief introduction to the language.

If you are a budding analyst or want to freshen up on your concepts, this book is for you. It has all the basic information you need to help you become a data analyst or scientist.

© 2022 Alex Published (หนังสือเสียง ): 9798822652842

วันที่วางจำหน่าย

หนังสือเสียง : 16 พฤศจิกายน 2565

คนอื่นก็สนุก...

  1. Data Science John D. Kelleher
  2. Data Analysis Introbooks Team
  3. Data Visualization: Ultimate Guide to Data Mining and Visualization. Alex Campbell
  4. Data Science for Beginners: Comprehensive Guide to Most Important Basics in Data Science Alex Campbell
  5. Learning from Data Introbooks Team
  6. Data Visualization Guide: Clear Introduction to Data Mining, Analysis, and Visualization Alex Campbell
  7. Big Data, Little Data, No Data: Scholarship in the Networked World Christine L. Borgman
  8. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking Foster Provost
  9. Data Mesh: What Is Data Mesh? Principles of Data Mesh Architecture Brian Murray
  10. Data Science For Dummies: 2nd Edition Lillian Pierson
  11. Crash Course Big Data Introbooks Team
  12. Python For Data Science: The Ultimate Comprehensive Step-By-Step Guide To The Basics Of Python For Data Science Kevin Clark
  13. Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses Michele Chambers
  14. Big Data Revolution: What farmers, doctors and insurance agents teach us about discovering big data patterns Rob Thomas
  15. Fundamentals of Data Engineering: Plan and Build Robust Data Systems Matt Housley
  16. Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals Brent Dykes
  17. Big Data Analytics: Turning Big Data into Big Money Frank J. Ohlhorst
  18. Data and Databases: Learn Data Analytics, Data Mining, and Operating Systems (2 in 1) Jonathan Rigdon
  19. Data Analyses: Detailed, Scientific, and Business-Oriented Data Reading Skills Benjamin Farrar
  20. The Creativity Code: How AI is learning to write, paint and think Marcus du Sautoy
  21. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management Michael J. A. Berry
  22. Artificial Intelligence For Dummies Luca Massaron
  23. Data Mesh: Delivering Data-Driven Value at Scale Zhamak Dehghani
  24. 101 Amazing Statistics Jack Goldstein
  25. Business Intelligence For Dummies Swain Scheps
  26. Coders: Who They Are, What They Think and How They Are Changing Our World Clive Thompson
  27. How Smart Machines Think Sean Gerrish
  28. A Little History of Economics Niall Kishtainy
  29. The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity Byron Reese
  30. Machine Learning: Deep Learning, Text Analytics, and Reinforcement Learning with Big Data David Feldspar
  31. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World Karim R. Lakhani
  32. AI and Genius Machines Scientific American
  33. Deep Learning: Machine Learning and Data Analytics Explained David Feldspar
  34. The AI Delusion Gary Smith
  35. Deep Learning John D. Kelleher
  36. Human Universe Professor Brian Cox
  37. The Number Mysteries: A Mathematical Odyssey through Everyday Life Marcus du Sautoy
  38. Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets Nassim Nicholas Taleb
  39. Range: How Generalists Triumph in a Specialized World David Epstein
  40. On the Future: Prospects for Humanity Martin Rees
  41. Permanent Record: A Memoir of a Reluctant Whistleblower Edward Snowden
  42. Coding for Beginners Using Python: A HANDS-ON, PROJECT-BASED INTRODUCTION TO LEARN CODING WITH PYTHON MARK MATTHES AND ERIC LUTZ
  43. HBR's 10 Must Reads on Strategy (including featured article "What Is Strategy?" by Michael E. Porter) W. Chan Kim
  44. The Knowledge Illusion: The myth of individual thought and the power of collective wisdom Philip Fernbach

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