Introducing Data Science – Davy Cielen & Arno D.B.Meysman & Mohamed Ali

The illustration on the cover of Introducing Data Science is taken from the 1805 edition of Sylvain Maréchal’s four-volume compendium of regional dress customs. This book was first published in Paris in 1788, one year before the French Revolution. Each illustration is colored by hand. The caption for this illustration reads “Homme Salamanque,” which means man from Salamanca, a province in western Spain, on the border with Portugal. The region is known for its wild beauty, lush forests, ancient oak trees,
rugged mountains, and historic old towns and villages.

The Homme Salamanque is just one of many figures in Maréchal’s colorful collection. Their diversity speaks vividly of the uniqueness and individuality of the world’s towns and regions just 200 years ago. This
was a time when the dress codes of two regions separated by a few dozen miles identified people uniquely as belonging to one or the other. The collection brings to life a sense of the isolation and distance of that
period and of every other historic period—except our own hyperkinetic present. Dress codes have changed since then and the diversity by region, so rich at the time, has faded away. It is now often hard to tell the inhabitant of one continent from another. Perhaps we have traded cultural diversity for a more varied personal life-certainly for a more varied and fast-paced technological life.

We at Manning celebrate the inventiveness, the initiative, and the fun of the computer business with book covers based on the rich diversity of regional life two centuries ago, brought back to life by Maréchal’s pictures.

Related posts:

Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Introduction to the Math of Neural Networks - Jeff Heaton
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Deep Learning and Neural Networks - Jeff Heaton
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Amazon Machine Learning Developer Guild Version Latest
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Deep Learning with Theano - Christopher Bourez
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Intelligent Projects Using Python - Santanu Pattanayak
Deep Learning with Hadoop - Dipayan Dev
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
R Deep Learning Essentials - Dr. Joshua F.Wiley
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Deep Learning with PyTorch - Vishnu Subramanian
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Machine Learning with Python for everyone - Mark E.Fenner
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Medical Image Segmentation Using Artificial Neural Networks