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Practical Guide to Becoming a Data Scientist: A Real Life Project Based Approach

by Olumide Olufowobi
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Current price ₹2,248.00
Original price ₹2,450.00
Original price ₹2,450.00
Original price ₹2,450.00
(-8%)
₹2,248.00
Current price ₹2,248.00

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Book cover type: Paperback
  • ISBN13: 9781660368808
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 334
  • Original Price: USD 25.0
  • Language: English
  • Edition: N/A
  • Item Weight: 490 grams
  • BISAC Subject(s): Computers & Technology

This book presents the best practical guide to gaining the necessary skills required in data science. These include Python, Machine Learning, Machine Learning Mathematical Techniques, SQL, Cloud-based and On-premises Database Techniques.Data science is currently the most sought-after career and no doubt the most ubiquitous disruptive technology.Any business or organization that aims at remaining competitive- not just being competitively equal but unique, in the face of the present challenges must tap into the opportunities presented by data science.Individual aspiring to become successful in data science must have thorough knowledge of the necessary skills that help in turning business or organization questions into data science questions, and solving the questions, using analytics tool.This book is presented in such a way that the knowledge of the required skills would be gained fast and deep.You will learn the following: -How to turn business or organization question into data science question and solve the question using the appropriate data science analytical techniques.-Learn iPython, using Spyder IDE.-For those already familiar with Python, a project in this book presents advanced analytical techniques using Python.-Query languages- SQL, PostgreSQL and SQLite.-Database handing techniques. Both on-premises and cloud-based techniques.-Machine Learning (ML) is the most mathematically sophisticated analytical tool. This book presents ML in such a way that you'll learn ML concepts, ML mathematical techniques and how to use these techniques to develop ML algorithms seamlessly.-The last part of this book reinforces the knowledge gained by presenting a real life complex, but methodically explained data science project. The approach is such that it would be easy to follow through.

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