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Book details
File Size: 7 MB
Format: pdf
Print Length: 230 pages
Page Numbers Source ISBN: 1484235967
Publisher: Apress; 1 edition (May 10, 2018)
Publication Date: May 10, 2018
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B07CZXR3YG
Who This Book Is For: The novice yearning to break into the data science world, and the enthusiast looking to enrich, deepen, and develop data science skills through mastering the underlying fundamentals that are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming will make learning easier.
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate. The book is a necessary precursor to applying and implementing machine learning algorithms.
The book is self-contained. All of the math, statistics, stochastic, and programming skills required to master the content are covered. In-depth knowledge of object-oriented programming isn’t required because complete examples are provided and explained.
Data Science Fundamentals with Python and MongoDB is an excellent starting point for those interested in pursuing a career in data science. Like any science, the fundamentals of data science are a prerequisite to competency. Without proficiency in mathematics, statistics, data manipulation, and coding, the path to success is “rocky” at best. The coding examples in this book are concise, accurate, and complete, and perfectly complement the data science concepts introduced.
What You’ll Learn
Prepare for a career in data science
Work with complex data structures in Python
Simulate with Monte Carlo and Stochastic algorithms
Apply linear algebra using vectors and matrices
Utilize complex algorithms such as gradient descent and principal component analysis
Wrangle, cleanse, visualize, and problem solve with data
Use MongoDB and JSON to work with data
For More Premium Graphics,Accounts,Freebies Visit >>> Forum.NulledPremium.com
Book details
File Size: 7 MB
Format: pdf
Print Length: 230 pages
Page Numbers Source ISBN: 1484235967
Publisher: Apress; 1 edition (May 10, 2018)
Publication Date: May 10, 2018
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B07CZXR3YG
Who This Book Is For: The novice yearning to break into the data science world, and the enthusiast looking to enrich, deepen, and develop data science skills through mastering the underlying fundamentals that are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming will make learning easier.
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate. The book is a necessary precursor to applying and implementing machine learning algorithms.
The book is self-contained. All of the math, statistics, stochastic, and programming skills required to master the content are covered. In-depth knowledge of object-oriented programming isn’t required because complete examples are provided and explained.
Data Science Fundamentals with Python and MongoDB is an excellent starting point for those interested in pursuing a career in data science. Like any science, the fundamentals of data science are a prerequisite to competency. Without proficiency in mathematics, statistics, data manipulation, and coding, the path to success is “rocky” at best. The coding examples in this book are concise, accurate, and complete, and perfectly complement the data science concepts introduced.
What You’ll Learn
Prepare for a career in data science
Work with complex data structures in Python
Simulate with Monte Carlo and Stochastic algorithms
Apply linear algebra using vectors and matrices
Utilize complex algorithms such as gradient descent and principal component analysis
Wrangle, cleanse, visualize, and problem solve with data
Use MongoDB and JSON to work with data