Supreme Ambitions details the rise of Audrey Coyne, a recent Yale Law School graduate who dreams of clerking for the U.S. Supreme Court someday. Audrey moves to California to clerk for Judge Christina Wong Stinson, a highly regarded appeals-court judge who is Audrey's ticket to a Supreme Court clerkship. While working for the powerful and driven Judge Stinson, Audrey discovers that high ambitions come with a high price. Toss in some headline-making cases, a little romance, and a pesky judicial gossip blog, and you have a legal novel with the inside scoop you'd expect from the founder of Above the Law, one of the nation's most widely read and influential legal websites.
Mohammad Nor Khalid, far better known as Lat, is Malaysia's top cartoonist. In Lat: My Life and Cartoons he tells for the first time the story of his life. From his childhood in the idyllic village atmosphere so evocatively captured by him in his bestselling book Kampung Boy, through his years as a crime reporter in 1970s Kuala Lumpur, and several decades as an editorial and freelance cartoonist, Lat has achieved celebrity status and won the hearts and attention of millions with his inimitable style and perceptive insights. Respected by cartoonists around the world and venerated by the Malaysian public, his cartoons have been translated into nine languages and his animated series Kampung Boy has been broadcast in many countries including Canada. This treasure trove of memories tells the story of a man whose cartoons have come to represent the collective memories of an entire country. The book is illustrated throughout with photographs, memorabilia and carefully selected cartoons.
A step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker Key FeaturesPerform ML experiments with built-in and custom algorithms in SageMakerExplore proven solutions when working with TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learnUse the different features and capabilities of SageMaker to automate relevant ML processesBook Description Amazon SageMaker is a fully managed machine learning (ML) service that helps data scientists and ML practitioners manage ML experiments. In this book, you'll use the different capabilities and features of Amazon SageMaker to solve relevant data science and ML problems. This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects. You'll cover the algorithms and techniques that are commonly used when training and deploying NLP, time series forecasting, and computer vision models to solve ML problems. You'll explore various solutions for working with deep learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers in Amazon SageMaker. You'll also learn how to use SageMaker Clarify, SageMaker Model Monitor, SageMaker Debugger, and SageMaker Experiments to debug, manage, and monitor multiple ML experiments and deployments. Moreover, you'll have a better understanding of how SageMaker Feature Store, Autopilot, and Pipelines can meet the specific needs of data science teams. By the end of this book, you'll be able to combine the different solutions you've learned as building blocks to solve real-world ML problems. What you will learnTrain and deploy NLP, time series forecasting, and computer vision models to solve different business problemsPush the limits of customization in SageMaker using custom container imagesUse AutoML capabilities with SageMaker Autopilot to create high-quality modelsWork with effective data analysis and preparation techniquesExplore solutions for debugging and managing ML experiments and deploymentsDeal with bias detection and ML explainability requirements using SageMaker ClarifyAutomate intermediate and complex deployments and workflows using a variety of solutionsWho this book is for This book is for developers, data scientists, and machine learning practitioners interested in using Amazon SageMaker to build, analyze, and deploy machine learning models with 80 step-by-step recipes. All you need is an AWS account to get things running. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.
The Latin Alive! Book One: Teacher's Edition includes a complete copy of the student text, as well as answer keys, extra teacher's notes and explanations, unit tests, and bonus projects and activities.