The big book of data science. Part I, Data processing / David Lopez, Eugenia Robles.

Format:

Book

Author/Creator:

Lopez, David, author.

Robles, Eugenia, author.

Language:

English

Subjects (All):

Artificial intelligence.

Information storage and retrieval systems.

Physical Description:

1 online resource (420 pages)

Edition:

[First edition].

Place of Publication:

[Place of publication not identified] : Cyberblue Media, [2025]

Summary:

There are already excellent books on software programming for data processing and data transformation for instance: Wes McKinney's. This book, reflecting on my own industrial and teaching experience, tries to overcome the big learning curve newcomers to the field have to travel before they are ready to tackle real data science and AI challenges. In this regard this book is different to other books in that: It assumes zero software programming knowledge. This instructional design is intentional given the book's aim to open the practice of data science to anyone interested in data exploration and analysis irrespective of their previous background. It follows an incremental approach to facilitate the assimilation of, sometimes, arcane software techniques to manipulate data. It is practice oriented to ensure readers can apply what they learn in their daily practices. Illustrates how to use generative AI to help you become a more productive data scientist and AI engineer. By reading and working on the labs included in this book you will develop software programming skills required to successfully contribute to the data understanding and data preparation stages involved in any data related project. You will become proficient at manipulating and transforming datasets in industrial contexts and produce clean, reliable datasets that can drive accurate analysis and informed decision-making. Moreover you will be prepared to develop and deploy dashboards and visualizations supporting the insights and conclusions in the deployment stage. Data modelling and evaluation are not covered in this book. We are working on a second installment of the book series illustrating the application of statistical and machine learning techniques to derive data insights.

Notes:

OCLC-licensed vendor bibliographic record.

ISBN:

979-89-93039-40-4

OCLC:

1535209416