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AWS Certified Machine Learning Study Guide
Author Shreyas Subramanian , Stefan Natu
Succeed on the AWS Machine Learning exam or in your next job as a machine learning specialist on the AWS Cloud platform with this hands-on guide As the most popular cloud service in the world today, Amazon Web Services offers a wide range of opportun....
Release Date 2021/12 -
Author Andre Ye
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learnin....
Release Date 2021/11 -
Data-Driven Alexa Skills: Voice Access to Rich Data Sources for Enterprise Applications
Author Simon A. Kingaby
Design and build innovative, custom, data-driven Alexa skills for home or business. Working through several projects, this book teaches you how to build Alexa skills and integrate them with online APIs. If you have basic Python skills, this book will show you how to build data-driven Alexa skills. Y....
Release Date 2021/11 -
Real-World Natural Language Processing
Author Masato Hagiwara
Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you’ll create many interesting applications including a sentiment analyzer and a chatbot....
Release Date 2021/11 -
Machine Learning Engineering with Python
Author Andrew P. McMahon
Supercharge the value of your machine learning models by building scalable and robust solutions that can serve them in production environmentsKey FeaturesExplore hyperparameter optimization and model management toolsLearn object-oriented programming and functional programming in Python to build your....
Release Date 2021/11 -
Natural Language Processing with AWS AI Services
Author Mona M , Premkumar Rangarajan , Julien Simon
Work through interesting real-life business use cases to uncover valuable insights from unstructured text using AWS AI servicesKey FeaturesGet to grips with AWS AI services for NLP and find out how to use them to gain strategic insightsRun Python code to use Amazon Textract and Amazon Comprehend to ....
Release Date 2021/11 -
Learn Amazon SageMaker - Second Edition
Author Julien Simon
Swiftly build and deploy machine learning models without managing infrastructure and boost productivity using the latest Amazon SageMaker capabilities such as Studio, Autopilot, Data Wrangler, Pipelines, and Feature StoreKey FeaturesBuild, train, and deploy machine learning models quickly using Amaz....
Release Date 2021/11 -
Author KC Tung
This easy-to-use reference for Tensorflow 2 pattern designs in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow....
Release Date 2021/10 -
Fundamentals of Deep Learning, 2nd Edition
We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception that has powered our push toward self-driving vehicles, the ability to defeat human experts at a variety of difficult games including Go and Starcraft, and even generate essays with shockingly coherent .... -
Author Olivier Le Deuff
The term "hyperdocumentation" is a hyperbole that seems to characterize a paradox. The leading discussions on this topic bring in diverse ideas such as that of data, the fantasy of Big Data, cloud computing, artificial intelligence, algorithmic processing, the flow of information and t....
Release Date 2021/09 -
The Framework for ML Governance
Most companies don't have problems building and deploying algorithmic models, but they do struggle to effectively manage them in production. Maximizing the value of machine learning projects in the enterprise requires a robust MLOps program. But there's one key challenge: The problem MLOps sets ou.... -
AI and Machine Learning for On-Device Development
AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating and running models on popular mobile platforms such as iOS and A.... -
Beginning Azure Cognitive Services: Data-Driven Decision Making Through Artificial Intelligence
Get started with Azure Cognitive Services and its APIs that expose machine learning as a service. This book introduces the suite of Azure Cognitive Services and helps you take advantage of the proven machine learning algorithms that have been developed by experts and made available through Cognitive.... -
Author Joe Papa
This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the t....
Release Date 2021/08 -
Transfer Learning for Natural Language Processing
Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions quickly by building on existing pretrained models. This instantly useful book provides crystal-clear explanations of the concepts you need to grok transfer learning along with hands-on examples so you can .... -
Multiply Your Business Value Through Brand & AI
Brand building is a competitive advantage that organizations can leverage to multiply their value. Artificial intelligence (AI), is a recent phenomenon that enables organizations reduce errors, build efficiencies and increase profitability, thereby freeing their human capital to perform more intelle.... -
Machine Learning Engineering with MLflow
Get up and running, and productive in no time with MLflow using the most effective machine learning engineering approachKey FeaturesExplore machine learning workflows for stating ML problems in a concise and clear manner using MLflowUse MLflow to iteratively develop a ML model and manage it Discover.... -
Deep Learning for Chest Radiographs
Author Yashvi Chandola , Jitendra Virmani , H.S Bhadauria , Papendra Kumar
Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectio....
Release Date 2021/07 -
Installing and Configuring IBM Db2 AI for IBM z/OS v1.4.0
Artificial intelligence (AI) enables computers and machines to mimic the perception, learning, problem-solving, and decision-making capabilities of the human mind. AI development is made possible by the availability of large amounts of data and the corresponding development and wide availability of .... -
Practical Machine Learning for Computer Vision
This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with prove.... -
Generating a New Reality : From Autoencoders and Adversarial Networks to Deepfakes
The emergence of artificial intelligence (AI) has brought us to the precipice of a new age where we struggle to understand what is real, from advanced CGI in movies to even faking the news. AI that was developed to understand our reality is now being used to create its own reality. In thi.... -
Towards Sustainable Artificial Intelligence: A Framework to Create Value and Understand Risk
So far, little effort has been devoted to developing practical approaches on how to develop and deploy AI systems that meet certain standards and principles. This is despite the importance of principles such as privacy, fairness, and social equality taking centre stage in discussions around AI..... -
Human-in-the-Loop Machine Learning
Human-in-the-Loop Machine Learning lays out methods for humans and machines to work together effectively. You’ll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You’ll learn to create training data for label....