Journey through the theory and practice of modern deep learning, and apply innovative techniques to solve everyday data problems. In Inside Deep Learning, you will learn how to: Implement deep learning with PyTorch Select the right deep learning components Train and evaluate a deep learning model Fine tune deep learning models to maximize performance Understand deep learning terminology Adapt existing PyTorch code to solve new problems Inside Deep...

Everything you need to know to get started as an adult learning professional. Instructing adults is dramatically different from teaching children, and the effectiveness of training programs is often dictated by how well they apply the principles of adult learning. Enhance your programs with the latest research into how adults learn, remember, and apply knowledge and skills. Adult Learning Basics examines the principles of adult learning theory and...

Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced...

Today, All Learning Is Blended Learning Modern learning audiences want flexibility and personalization--development on their terms. They need a blended approach to learning that lets them grow their skills and knowledge where they actually perform their work. When designed and implemented effectively, blended learning can breathe life back into your talent development offerings. Blended Learning is packed with easy-to-apply techniques to ensure your...

Leverage top XAI frameworks to explain your machine learning models with ease and discover best practices and guidelines to build scalable explainable ML systems Key Features Explore various explainability methods for designing robust and scalable explainable ML systems Use XAI frameworks such as LIME and SHAP to make ML models explainable to solve practical problems Design user-centric explainable ML systems using guidelines provided for industrial...

"Adobe Premiere Pro: a complete course and compendium' is your guide to creating, editing, and enhancing videos in Adobe Premiere Pro. Whether you're organizing hours of interview, rapidly splicing news clips before a deadline, or creating your magnum opus, Premiere Pro in the tool for you--and this book will teach you what you need to know."--back cover.

Machine Learning Systems: Designs that scale is an example-rich guide that teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. About the Technology If you're building machine learning models to be used on a small scale, you don't need this book. But if you're a developer building a production-grade ML application that needs quick response times, reliability, and...

Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft's powerful ML.NET library, including capabilities for data processing,...