The Paytech Book

The PayTech Book: The Payment Technology Handbook for Investors, Entrepreneurs, and FinTech Visionaries

Susanne Chishti, "The PayTech Book: The Payment Technology Handbook for Investors, Entrepreneurs, and FinTech Visionaries"
English | ISBN: 1119551919 | 2020 | 256 pages | PDF | 7 MB
The PAYTECH Book: The Payment Technology Handbook for Investors, Entrepreneurs, and FinTech Visionaries

The PAYTECH Book: The Payment Technology Handbook for Investors, Entrepreneurs, and FinTech Visionaries by Susanne Chishti, Tony Craddock, Robert Courtneidge, Markos Zachariadis
English | January 24th, 2020 | ISBN: 1119551919 | 256 pages | EPUB | 4.63 MB

The only globally-crowdsourced book on the future of payments (“PayTech”), offering comprehensive understanding of a rapidly evolving industry at the centre of global commerce
The LegalTech Book: The Legal Technology Handbook for Investors, Entrepreneurs and FinTech Visionaries

The LegalTech Book: The Legal Technology Handbook for Investors, Entrepreneurs and FinTech Visionaries by Sophia Adams Bhatti, Akber Datoo, Drago Indjic
English | June 7th, 2020 | ISBN: 1119574277 | 282 pages | True EPUB | 2.64 MB

Written by prominent thought leaders in the global fintech and legal space, The LegalTech Book aggregates diverse expertise into a single, informative volume. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned.

Data Science: The Hard Parts: Techniques for Excelling at Data Science  eBooks & eLearning

Posted by First1 at Nov. 11, 2023
Data Science: The Hard Parts: Techniques for Excelling at Data Science

Data Science: The Hard Parts: Techniques for Excelling at Data Science by Daniel Vaughan
English | December 5th, 2023 | ISBN: 1098146476 | 254 pages | True EPUB | 5.55 MB

This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline—machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one.