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:

Pro Deep Learning with TensorFlow - Santunu Pattanayak
Intelligent Projects Using Python - Santanu Pattanayak
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Python Deep Learning Cookbook - Indra den Bakker
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Deep Learning with Python - Francois Cholletf
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning in Python - LazyProgrammer
Machine Learning with Python for everyone - Mark E.Fenner
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
The hundred-page Machine Learning Book - Andriy Burkov
Deep Learning with Python - Francois Chollet
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Neural Networks - A visual introduction for beginners - Michael Taylor
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Pattern recognition and machine learning - Christopher M.Bishop
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Neural Networks and Deep Learning - Charu C.Aggarwal
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron