The Big Book of Data Science. Part I: Data by David Lopez (.ePUB)

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File Size: 10 MB

The Big Book of Data Science. Part I: Data Processing by David Lopez, Eugenia Robles
Requirements: .ePUB reader, 10 MB
Overview: 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. The Python versus R debate is as old as the field of data science with yet new languages (e.g. Julia, Rust, Scala) joining the fray. Each language has its own strengths and weaknesses, and the right choice really depends on what you’re trying to accomplish. Are you in need of real time analytics? Do you need highly specialized numerical applications? Python has emerged as the leading language in Data Science and AI primarily due to its simplicity and readability. Its clean syntax allows data scientists and analysts to write and understand code quickly, which is essential when dealing with complex data analyses. This ease of use significantly lowers the barrier for newcomers, enabling them to focus on data interpretation and insight generation rather than getting bogged down by intricate coding nuances. 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.
Genre: Non-Fiction > Tech & Devices

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