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PYTHON DATA SCIENCE

A Practical Guide to Mastering Python for Data Science and Artificial Intelligence (2023 Beginner Crash Course)

Calvert Long

EPUB
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Calvert Long img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik, EDV

Beschreibung

Python has become one of the most popular programming languages for data science and artificial intelligence. It's a versatile language that offers a wide range of libraries and tools for data analysis, visualization, and machine learning. In this book, "Python Data Science," readers will learn how to use Python to explore and analyze data, create powerful visualizations, and build machine learning models.


This book features:

  • A practical guide to Python data science, covering everything from data cleaning and manipulation to statistical analysis and machine learning
  • A comprehensive overview of popular Python libraries for data science, including NumPy, Pandas, Matplotlib, and Scikit-Learn
  • Step-by-step tutorials with real-world examples and hands-on exercises
  • Strategies for working with large datasets and optimizing code for speed and efficiency
  • Best practices for data visualization and interpretation
  • A complete introduction to machine learning with Python, covering supervised and unsupervised learning, deep learning, and natural language processing
  • Guidance on choosing the right algorithms and models for your specific data and business problems

And Much More!...


Whether you're a beginner or an experienced programmer looking to expand your skills, "Python Data Science" offers a comprehensive guide to mastering Python for data science and artificial intelligence. With this book, you'll be able to analyze and interpret data, build predictive models, and make data-driven decisions with confidence.

 

So, scroll up and click the "Buy Now" button to get this book!!!

Kundenbewertungen

Schlagwörter

Software development, Data Wrangling, Mobile app development, Data Mining, Data Visualization, Data Analysis, Artificial Intelligence, Statistical Analysis, Object-oriented programming, Natural Language Processing, Programming languages, Machine Learning, Web Scraping, Web development, Big Data