The Plains of Howling Darkness Dave Morris 1995
Paper Cut Owen Gildersleeve 2014-06-01 Paper Cut offers a unique perspective into one of the most exciting fields of contemporary illustration. You'll discover amazing creations from thirty of the top papercraft illustrators from around the globe. Showcasing their astonishing works and discussing their creative processes, this collection of artists' words and works will awe and inspire you. Author Owen Gildersleeve - himself a recognised paper craftsman - explores why these artists love paper, how they use it and what makes their work so unique.
Papercraft Christmas Ellen Giggenbach 2014-10 In this book, collage artist Ellen Giggenbach has brought together twenty of her favourite Christmas papercraft projects, including baubles, wall decorations and 3-D models, for you to make during the festive season. Each page is removable, with cut and fold guides and assembly instructions. Once you have made a model featuring Ellen Giggenbach's illustrations, you can then try a plain paper version and add extra collage elements using the stickers provided. Get the papercrafting bug! AGES: 7+ years AUTHOR: Ellen Giggenbach is a Kiwi who was born in Bavaria, Germany. She feels that her German heritage adds an element of folk art to her work. Using old stationery, wallpaper and fabric, Ellen creates each of her unashamedly decorative and joyful collages by hand. SELLING POINTS: * Create 20 colourful papercraft festive decorations from the pull-out pages * Also includes over 200 collage stickers to decorate * Turn the cover into a folder for work-in-progress following the guide included ***NOVELTY TITLE***
Data Science Fundamentals and Practical Approaches Dr. Gypsy Nandi 2020-06-02 Learn how to process and analysis data using Python KEY FEATURES - The book has theories explained elaborately along with Python code and corresponding output to support the theoretical explanations. The Python codes are provided with step-by-step comments to explain each instruction of the code. - The book is not just dealing with the background mathematics alone or only the programs but beautifully correlates the background mathematics to the theory and then finally translating it into the programs. - A rich set of chapter-end exercises are provided, consisting of both short-answer questions and long-answer questions. DESCRIPTION This book introduces the fundamental concepts of Data Science, which has proved to be a major game-changer in business solving problems. Topics covered in the book include fundamentals of Data Science, data preprocessing, data plotting and visualization, statistical data analysis, machine learning for data analysis, time-series analysis, deep learning for Data Science, social media analytics, business analytics, and Big Data analytics. The content of the book describes the fundamentals of each of the Data Science related topics together with illustrative examples as to how various data analysis techniques can be implemented using different tools and libraries of Python programming language. Each chapter contains numerous examples and illustrative output to explain the important basic concepts. An appropriate number of questions is presented at the end of each chapter for self-assessing the conceptual understanding. The references presented at the end of every chapter will help the readers to explore more on a given topic. WHAT WILL YOU LEARN Perform processing on data for making it ready for visual plot and understand the pattern in data over time. Understand what machine learning is and how learning can be incorporated into a program. Know how tools can be used to perform analysis on big data using python and other standard tools. Perform social media analytics, business analytics, and data analytics on any data of a company or organization. WHO THIS BOOK IS FOR The book is for readers with basic programming and mathematical skills. The book is for any engineering graduates that wish to apply data science in their projects or wish to build a career in this direction. The book can be read by anyone who has an interest in data analysis and would like to explore more out of interest or to apply it to certain real-life problems. TABLE OF CONTENTS 1. Fundamentals of Data Science1 2. Data Preprocessing 3. Data Plotting and Visualization 4. Statistical Data Analysis 5. Machine Learning for Data Science 6. Time-Series Analysis 7. Deep Learning for Data Science 8. Social Media Analytics 9. Business Analytics 10. Big Data Analytics

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