Python for Data Analysis: The Top Guide for Beginners to Discovering Data Science from Scratch, Data Analysis, Analytics & Machine Learning using Python with Business Cases – 4 Books in 1 - KING OF EXCEL

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Saturday, February 27, 2021

Python for Data Analysis: The Top Guide for Beginners to Discovering Data Science from Scratch, Data Analysis, Analytics & Machine Learning using Python with Business Cases – 4 Books in 1

 

Python for Data Analysis: The Top Guide for Beginners to Discovering Data Science from Scratch, Data Analysis, Analytics & Machine Learning using Python with Business Cases – 4 Books in 1

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by DataAndCode Academy
  • Length: 270 pages
  • Edition: 1
  • Publication Date: 2021-02-19

Are You Looking For The Best Beginners Guide To Discovering Data Analysis And Analytics With Python?

Do You Want To Enter The World Of Data Science And How To Leverage Python For It?

Do Want To Get A Thorough Introduction To Machine Learning?

If yes, then this Guide is for you! This is the Top Guide to learning Data Analysis & Analytics, Data Science and Machine Learning with 4 Manuscripts in 1 book:

  1. Python for Data Analysis & Analytics
  2. Data Science Core
  3. Data Science Annex
  4. Machine Learning Introduction.

A great opportunity: Simplicity, Best Order and Selection of topics to Learn Fast and Selected Practice Exercises and Examples.

In Manuscript 1 “Python for Data Analysis & Analytics” you’ll discover:

  • What Data Analysis is and why it is important
  • What are the different types of Data Analysis
  • What are the 6 key steps of the Data Analysis process that you should follow
  • What are the applications of Data Analysis and Analytics
  • How to set up the Python environment for Data Analysis
  • What are and how to use Python Data Structures
  • How to work with IPython/Jupyter Notebook
  • How to work with NumPy
  • How to visualize data with Matplotlib
  • What other visualization libraries are out there

In Manuscript 2 “Data Science Core” you’ll discover:

  • What is Data Science and what does it encompass
  • What are the 5 key steps of the Data Science process that you should follow
  • How to set up the Python environment for Data Science
  • How to work with Seaborn data visualization module
  • How to leverage the Scikit-Learn module for Machine Learning
  • How to leverage Data Science in the Cloud

In Manuscript 3 “Data Science Annex” you’ll discover:

  • What are the most important applications of Data Science
  • What are the most important Machine Learning Algorithms
  • Why is Big Data important and how to get the best out of it
  • How to leverage Neural Networks
  • What are the main Data Mining Techniques
  • And much more…

In Manuscript 4 “Machine Learning Introduction” you’ll discover

  • What is Machine Learning and what does it encompass
  • What are the 7 Steps of the Machine Learning Process
  • What are the different Machine Learning types
  • How is Machine Learning applied to the real world
  • What are the most important Python libraries for Machine Learning
  • And much more…
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