Practical Data Science With Jupyter

By:

Gupta, Prateek

Material type: Text

TextLanguage: English Publication details: New Delhi : Bpb Publications, 2021Edition: 2Description: 341ISBN:

9789389898064

Subject(s):

DDC classification:

006.31 GUP

Summary: Solve business problems with data-driven techniques and easy-to-follow Python examplesKey FeaturesEssential coverage on statistics and data science techniques.Exposure to Jupyter, PyCharm, and use of GitHub.Real use-cases, best practices, and smart techniques on the use of data science for data applications.DescriptionThis book begins with an introduction to Data Science followed by the Python concepts. The readers will understand how to interact with various database and Statistics concepts with their Python implementations. You will learn how to import various types of data in Python, which is the first step of the data analysis process. Once you become comfortable with data importing, you will clean the dataset and after that will gain an understanding about various visualization charts. This book focuses on how to apply feature engineering techniques to make your data more valuable to an algorithm. The readers will get to know various Machine Learning Algorithms, concepts, Time Series data, and a few real-world case studies. This book also presents some best practices that will help you to be industry-ready. This book focuses on how to practice data science techniques while learning their concepts using Python and Jupyter. This book is a complete answer to the most common question that how can you get started with Data Science instead of explaining Mathematics and Statistics behind the Machine Learning Algorithms.What you will learn Rapid understanding of Python concepts for data science applications.

List(s) this item appears in: New Arrivals for the Month of March 2023 - Computer Science and Data Science | New Arrivals for the Month of August - 2023

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Book	Alliance College of Engineering and Design	CSE & IT	006.31 GUP (Browse shelf(Opens below))	Checked out	03/01/2025	E12027
Book	Alliance School of Liberal Arts		006.31 GUP (Browse shelf(Opens below))	Available		LA01308

Total holds: 0

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Solve business problems with data-driven techniques and easy-to-follow Python examplesKey FeaturesEssential coverage on statistics and data science techniques.Exposure to Jupyter, PyCharm, and use of GitHub.Real use-cases, best practices, and smart techniques on the use of data science for data applications.DescriptionThis book begins with an introduction to Data Science followed by the Python concepts. The readers will understand how to interact with various database and Statistics concepts with their Python implementations. You will learn how to import various types of data in Python, which is the first step of the data analysis process. Once you become comfortable with data importing, you will clean the dataset and after that will gain an understanding about various visualization charts. This book focuses on how to apply feature engineering techniques to make your data more valuable to an algorithm. The readers will get to know various Machine Learning Algorithms, concepts, Time Series data, and a few real-world case studies. This book also presents some best practices that will help you to be industry-ready. This book focuses on how to practice data science techniques while learning their concepts using Python and Jupyter. This book is a complete answer to the most common question that how can you get started with Data Science instead of explaining Mathematics and Statistics behind the Machine Learning Algorithms.What you will learn Rapid understanding of Python concepts for data science applications.

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