Practical Data Science with Python 3: Synthesizing Actionable Insights from Data

Author:   Ervin Varga
Publisher:   APress
Edition:   1st ed.
ISBN:  

9781484248584


Pages:   462
Publication Date:   08 September 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Our Price $49.99 Quantity:  
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Practical Data Science with Python 3: Synthesizing Actionable Insights from Data


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Overview

Gain insight into essential data science skills in a holistic manner using data engineering and associated scalable computational methods. This book covers the most popular Python 3 frameworks for both local and distributed (in premise and cloud based) processing. Along the way, you will be introduced to many popular open-source frameworks, like, SciPy, scikitlearn, Numba, Apache Spark, etc. The book is structured around examples, so you will grasp core concepts via case studies and Python 3 code. As data science projects gets continuously larger and more complex, software engineering knowledge and experience is crucial to produce evolvable solutions. You'll see how to create maintainable software for data science and how to document data engineering practices. This book is a good starting point for people who want to gain practical skills to perform data science. All the code willbe available in the form of IPython notebooks and Python 3 programs, which allow you to reproduce all analyses from the book and customize them for your own purpose. You'll also benefit from advanced topics like Machine Learning, Recommender Systems, and Security in Data Science. Practical Data Science with Python will empower you analyze data, formulate proper questions, and produce actionable insights, three core stages in most data science endeavors. What You'll Learn Play the role of a data scientist when completing increasingly challenging exercises using Python 3 Work work with proven data science techniques/technologies  Review scalable software engineering practices to ramp up data analysis abilities in the realm of Big Data Apply theory of probability, statistical inference, and algebra to understand the data sciencepractices Who This Book Is For Anyone who would like to embark into the realm of data science using Python 3.

Full Product Details

Author:   Ervin Varga
Publisher:   APress
Imprint:   APress
Edition:   1st ed.
Weight:   0.730kg
ISBN:  

9781484248584


ISBN 10:   1484248589
Pages:   462
Publication Date:   08 September 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1.Introduction to Data Science.- Chapter 2.Data Acquisition.- Chapter 3.Basic Data Processing.- Chapter 4.Documenting Work.- Chapter 5.Transformation and Packaging of Data.- Chapter 6.Visualization.- Chapter 7.Prediction and Inference.- Chapter 8.Network Analysis.- Chapter 9.Data Science Process Engineering.- Chapter 10. Multi-agent Systems, Game Theory and Machine Learning.- Chapter 11. Probabilistic Graphical Models.- Chapter 12. Security in Data Science.

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Author Information

Ervin Varga is a Senior Member of IEEE and Professional Member of ACM. He is an IEEE Software Engineering Certified Instructor. Ervin is an owner of the software consulting company Expro I.T. Consulting, Serbia. He has an MSc in computer science, and a PhD in electrical engineering (his thesis was an application of software engineering and computer science in the domain of electrical power systems). Ervin is also a technical advisor of the open-source project Mainflux.

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