Generative Ai A Comprehensive Guide To Mastering Generative Ai Understanding The Essentials And Applications Of This Breakthrough Technology
Download Generative Ai A Comprehensive Guide To Mastering Generative Ai Understanding The Essentials And Applications Of This Breakthrough Technology PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Generative Ai A Comprehensive Guide To Mastering Generative Ai Understanding The Essentials And Applications Of This Breakthrough Technology book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Generative Ai: A Comprehensive Guide to Mastering Generative Ai (Understanding the Essentials and Applications of This Breakthrough Technology)
This book also delves into the ethical considerations and challenges associated with implementing generative ai, providing readers with a balanced perspective on its impact on society and the workforce. By exploring the role of leadership in harnessing generative ai for organizational success, readers will gain valuable insights into how to navigate this rapidly evolving landscape. Whether you're a business leader seeking to unlock the potential of generative ai for your organization or a technology enthusiast eager to explore its applications across industries, this book offers a comprehensive overview of one of the most exciting developments in artificial intelligence today. You will unravel valuable insights: • A deep dive into the ethical frameworks needed for responsible ai deployment in your organization • Actionable tips to integrate ai seamlessly into your existing workflow • Unparalleled case studies from businesses that have successfully tapped into the ai advantage • A toolkit to leverage competitive intelligence insights through ai • A crystal-clear demystification of common misconceptions surrounding ai • A practical ai vocabulary that every business leader should know In this book, i will provide you with a comprehensive overview of generative ai, including the underlying principles and the latest trends in the field. I will also show you how to apply generative ai to a variety of tasks and applications in your business as well as various other industries responsibly and safely. One of the key benefits of generative ai is its ability to learn from massive realms of data and generate new, unseen data.
Learning Deep Learning
Author: Magnus Ekman
language: en
Publisher: Addison-Wesley Professional
Release Date: 2021-07-19
NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals." -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA "Ekman uses a learning technique that in our experience has proven pivotal to success—asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us." -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience. After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images. Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning. Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation See how DL frameworks make it easier to develop more complicated and useful neural networks Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences Master NLP with sequence-to-sequence networks and the Transformer architecture Build applications for natural language translation and image captioning NVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Deep Learning With Python
Author: Jason Brownlee
language: en
Publisher: Machine Learning Mastery
Release Date: 2016-05-13
Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their power in a few lines of code using Keras, the best-of-breed applied deep learning library. In this Ebook, learn exactly how to get started and apply deep learning to your own machine learning projects.