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Automated Machine Learning in Action
Automated Machine Learning in Action reveals how you can automate the burdensome elements of designing and tuning your machine learning systems. --
Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications
This open access proceedings includes original, unpublished, peer-reviewed research papers from the International Conference on Wireless Communications, Networking and Applications (WCNA2021), held in Berlin, Germany on December 17-19th, 2021. The topics covered include but are not limited to wireless communications, networking and applications.The papers showcased here share the latest findings on methodologies, algorithms and applications in communication and network, making the book a valuable asset for professors, researchers, engineers, and university students alike. This is an open access book.
In Vitro Diagnostic Industry in China
This book systematically describes the achievements and current situation of in vitro diagnostic (IVD) industry in China. It consists of twelve parts, including the overview on the IVD industry in China in 2021, hot technologies and products of IVD industry, academic, technological and product development in the field of IVD, such as biochemical diagnosis, immune-diagnosis, point-of-care testing, molecular diagnosis, blood and body fluid diagnosis, microbial detection, laboratory assembly line, etc. In this second edition, the new contents added include the development of new coronavirus molecular diagnostic products, flight mass spectrometry, tandem mass spectrometry, tumor markers, ELISA i...
Practical Deep Learning for Cloud, Mobile, and Edge
Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users
Deep Learning with TensorFlow 2 and Keras
Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key FeaturesIntroduces and then uses TensorFlow 2 and Keras right from the startTeaches key machine and deep learning techniquesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesBook Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machin...
Sweetheart, You are so Attractive
Her bad superior had tried something on her, but she refused to obey until she died and got stripped of her position. However, in the elevator, the CEO actually kissed her and even made a contract with her ...
Daily Report
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Daily Report
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Data Mining
Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data, or KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducin...
