Books with author Nikki McClure

With dazzling, lyrical verse in the folk revival style and stunning cut-paper illustrations, Colin Meloy and Nikki McClure pay tribute to Pete Seeger, a visionary who changed the world with song. This nonfiction picture book is an excellent choice to share during homeschooling, in particular for children ages 4 to 6. It’s a fun way to learn to read and as a supplement for activity books for children.Pete Seeger once sang that if he had a golden thread, he would use it to weave people from all over the world to one another. That golden thread, for Pete, was music.Born into a family of traveling musicians, Pete picked up his first instrument at age seven. From then on, music was his life, whether he was playing banjo for soldiers during World War II, rallying civil rights activists and war protesters with songs such as “We Shall Overcome,” “Where Have All the Flowers Gone?,” and “If I Had a Hammer,” or leading environmental efforts to clean up the Hudson River.For decades, Pete Seeger’s messages of universal understanding and social and environmental justice inspired generations—and have left a lasting legacy.

Skip the theory and get the most out of Tensorflow to build production-ready machine learning modelsKey FeaturesExploit the features of Tensorflow to build and deploy machine learning modelsTrain neural networks to tackle real-world problems in Computer Vision and NLPHandy techniques to write production-ready code for your Tensorflow modelsBook DescriptionTensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before.With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production.By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.What you will learnBecome familiar with the basic features of the TensorFlow libraryGet to know Linear Regression techniques with TensorFlowLearn SVMs with hands-on recipesImplement neural networks to improve predictive modelingApply NLP and sentiment analysis to your dataMaster CNN and RNN through practical recipesImplement the gradient boosted random forest to predict housing pricesTake TensorFlow into productionWho this book is forIf you are a data scientist or a machine learning engineer with some knowledge of linear algebra, statistics, and machine learning, this book is for you. If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading pages and pages of material, this book is for you. Some background in Python programming is assumed.Table of ContentsGetting Started with TensorFlowThe TensorFlow WayLinear RegressionSupport Vector MachinesNearest Neighbor MethodsNeural NetworksNatural Language ProcessingConvolutional Neural NetworksRecurrent Neural NetworksTaking TensorFlow to ProductionMore with TensorFlow

Skip the theory and get the most out of Tensorflow to build production-ready machine learning modelsKey FeaturesExploit the features of Tensorflow to build and deploy machine learning modelsTrain neural networks to tackle real-world problems in Computer Vision and NLPHandy techniques to write production-ready code for your Tensorflow modelsBook DescriptionTensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production.By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.What you will learnBecome familiar with the basic features of the TensorFlow libraryGet to know Linear Regression techniques with TensorFlowLearn SVMs with hands-on recipesImplement neural networks to improve predictive modelingApply NLP and sentiment analysis to your dataMaster CNN and RNN through practical recipesImplement the gradient boosted random forest to predict housing pricesTake TensorFlow into productionWho this book is forIf you are a data scientist or a machine learning engineer with some knowledge of linear algebra, statistics, and machine learning, this book is for you. If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading pages and pages of material, this book is for you. Some background in Python programming is assumed. Table of ContentsGetting Started with TensorFlowThe TensorFlow WayLinear RegressionSupport Vector MachinesNearest Neighbor MethodsNeural NetworksNatural Language ProcessingConvolutional Neural NetworksRecurrent Neural NetworksTaking TensorFlow to ProductionMore with TensorFlow

This book describes "how to be a cat" through simple instructions; purr, stretch, explore, pounce, chase, while Nikki's distinctive paper cuts illustrate a kitten's attempts to imitate an adult cat's mastery of each skill. At times the kitten triumphantly succeeds in the instruction and at times he fumbles, creating a gently comic juxtaposition between text and image.