Books with author Robert Lawson

The master illustrator of Mr. Popper's Penguins and The Story of Ferdinand brings new life to a bevy of traditional tales. More than forty of the artist's enchanting pen-and-ink drawings grace thirteen fairy tales and poems of wizards, dragons, and princes in disguise by Padraic Colum, Beatrice Curtis Brown, Eunice Tietjens, and other distinguished authors. Contents include "Auntie Grumble Meets the Wizard" by Carol Johnstone Sharp; "Jonathan Bing Does Arithmetic," "More About Jonathan Bing," and "Jonathan Bing Dances for Spring" by Beatrice Curtis Brown; "The Pelican" by Mildred Plew Meigs; "The Wogg and the Baggle" by Laura E. Richards; and "The Man with the Bag" by Padraic Colum. Other features include Eunice Tietjens' "St. Valentine," "Story Tell" by Laura E. Richards, "The Little Dragon" by Constance Savery, Nancy Byrd Turner's "Planting a Tree," "Penguins" by Anne Brewer, and "The Piping on Christmas Eve" by Florence Page Jaques.

McWhinney's Jaunt is the amazing tale of an eccentric professor who accidentally creates z-gas, an almost magical substance that allows him to pedal his bicycle up into the air. He sets off a journey all over the United States of America and has many adventures. Beautifully illustrated by the brilliant Robert Lawson, this handsome new edition from Oxford City Press will delight younger readers and frequently raise a smile from the grown-ups as well.

Harness the power of Python to develop data mining applications, analyze data, delve into machine learning, explore object detection using Deep Neural Networks, and create insightful predictive models.Key FeaturesUse a wide variety of Python libraries for practical data mining purposes.Learn how to find, manipulate, analyze, and visualize data using Python.Step-by-step instructions on data mining techniques with Python that have real-world applications.Book DescriptionThis book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK.You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now.With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.What you will learnApply data mining concepts to real-world problemsPredict the outcome of sports matches based on past resultsDetermine the author of a document based on their writing styleUse APIs to download datasets from social media and other online servicesFind and extract good features from difficult datasetsCreate models that solve real-world problemsDesign and develop data mining applications using a variety of datasetsPerform object detection in images using Deep Neural NetworksFind meaningful insights from your data through intuitive visualizationsCompute on big data, including real-time data from the internetTable of ContentsGetting Started with Data MiningClassifying with scikit-learn EstimatorsPredicting Sports Winners with Decision TreesRecommending Movies Using Affinity AnalysisFeatures and scikit-learn TransformersSocial Media Insight using Naive BayesFollow Recommendations Using Graph MiningBeating CAPTCHAs with Neural NetworksAuthorship AttributionClustering News ArticlesObject Detection in Images using Deep Neural NetworksWorking with Big DataNext Steps...