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:

Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Python Machine Learning - Sebastian Raschka
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Artificial Intelligence by example - Denis Rothman
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Deep Learning with Python - Francois Chollet
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Machine Learning with spark and python - Michael Bowles
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Amazon Machine Learning Developer Guild Version Latest
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Python Machine Learning Eqution Reference - Sebastian Raschka
Deep Learning in Python - LazyProgrammer
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Introduction to the Math of Neural Networks - Jeff Heaton
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Coding Theory - Algorithms, Architectures and Application
The hundred-page Machine Learning Book - Andriy Burkov
Intelligent Projects Using Python - Santanu Pattanayak
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Neural Networks - A visual introduction for beginners - Michael Taylor
Medical Image Segmentation Using Artificial Neural Networks
Java Deep Learning Essentials - Yusuke Sugomori
Data Science and Big Data Analytics - EMC Education Services
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
An introduction to neural networks - Kevin Gurney & University of Sheffield
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron