H2o Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of H2o book. This book definitely worth reading, it is an incredibly well-written.
.27 is a number Ruby hates. It's a number that marks the percentage of the population that has survived. It's a number that means she's one of the "lucky" few still standing. And it's a number that says her father is probably dead. Against all odds, Ruby has survived the catastrophic onset of the killer rain. Two weeks after the radio started broadcasting the warning, "It's in the rain. It's fatal and there's no cure," the drinkable water is running out. Ruby's left with two options: persevere on her own, or embark on a treacherous journey across the country to find her father-if he's even still alive.
This book exhibits deep philosophical quandaries and intricacies of the historical development of science lying behind a simple and fundamental item of common sense in modern science, namely the composition of water as H2O. Three main phases of development are critically re-examined, covering the historical period from the 1760s to the 1860s: the Chemical Revolution (through which water first became recognized as a compound, not an element), early electrochemistry (by which water’s compound nature was confirmed), and early atomic chemistry (in which water started out as HO and became H2O). In each case, the author concludes that the empirical evidence available at the time was not decisive in settling the central debates and therefore the consensus that was reached was unjustified or at least premature. This leads to a significant re-examination of the realism question in the philosophy of science and a unique new advocacy for pluralism in science. Each chapter contains three layers, allowing readers to follow various parts of the book at their chosen level of depth and detail. The second major study in "complementary science", this book offers a rare combination of philosophy, history and science in a bid to improve scientific knowledge through history and philosophy of science.
Practical Machine Learning with H2O by Darren Cook Pdf
Machine learning has finally come of age. With H2O software, you can perform machine learning and data analysis using a simple open source framework that’s easy to use, has a wide range of OS and language support, and scales for big data. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms. If you’re familiar with R or Python, know a bit of statistics, and have some experience manipulating data, author Darren Cook will take you through H2O basics and help you conduct machine-learning experiments on different sample data sets. You’ll explore several modern machine-learning techniques such as deep learning, random forests, unsupervised learning, and ensemble learning. Learn how to import, manipulate, and export data with H2O Explore key machine-learning concepts, such as cross-validation and validation data sets Work with three diverse data sets, including a regression, a multinomial classification, and a binomial classification Use H2O to analyze each sample data set with four supervised machine-learning algorithms Understand how cluster analysis and other unsupervised machine-learning algorithms work
Machine Learning at Scale with H2O by Gregory Keys,David Whiting Pdf
Build predictive models using large data volumes and deploy them to production using cutting-edge techniques Key Features • Build highly accurate state-of-the-art machine learning models against large-scale data • Deploy models for batch, real-time, and streaming data in a wide variety of target production systems • Explore all the new features of the H2O AI Cloud end-to-end machine learning platform Book Description H2O is an open source, fast, and scalable machine learning framework that allows you to build models using big data and then easily productionalize them in diverse enterprise environments. Machine Learning at Scale with H2O begins with an overview of the challenges faced in building machine learning models on large enterprise systems, and then addresses how H2O helps you to overcome them. You'll start by exploring H2O's in-memory distributed architecture and find out how it enables you to build highly accurate and explainable models on massive datasets using your favorite ML algorithms, language, and IDE. You'll also get to grips with the seamless integration of H2O model building and deployment with Spark using H2O Sparkling Water. You'll then learn how to easily deploy models with H2O MOJO. Next, the book shows you how H2O Enterprise Steam handles admin configurations and user management, and then helps you to identify different stakeholder perspectives that a data scientist must understand in order to succeed in an enterprise setting. Finally, you'll be introduced to the H2O AI Cloud platform and explore the entire machine learning life cycle using multiple advanced AI capabilities. By the end of this book, you'll be able to build and deploy advanced, state-of-the-art machine learning models for your business needs. What you will learn • Build and deploy machine learning models using H2O • Explore advanced model-building techniques • Integrate Spark and H2O code using H2O Sparkling Water • Launch self-service model building environments • Deploy H2O models in a variety of target systems and scoring contexts • Expand your machine learning capabilities on the H2O AI Cloud Who this book is for This book is for data scientists and machine learning engineers who want to gain hands-on machine learning experience by building and deploying state-of-the-art models with advanced techniques using H2O technology. An understanding of the data science process and experience in Python programming is recommended. This book will also benefit students by helping them understand how machine learning works in real-world enterprise scenarios.
Practical Automated Machine Learning Using H2O.ai by Salil Ajgaonkar Pdf
Accelerate the adoption of machine learning by automating away the complex parts of the ML pipeline using H2O.ai Key FeaturesLearn how to train the best models with a single click using H2O AutoMLGet a simple explanation of model performance using H2O ExplainabilityEasily deploy your trained models to production using H2O MOJO and POJOBook Description With the huge amount of data being generated over the internet and the benefits that Machine Learning (ML) predictions bring to businesses, ML implementation has become a low-hanging fruit that everyone is striving for. The complex mathematics behind it, however, can be discouraging for a lot of users. This is where H2O comes in – it automates various repetitive steps, and this encapsulation helps developers focus on results rather than handling complexities. You'll begin by understanding how H2O's AutoML simplifies the implementation of ML by providing a simple, easy-to-use interface to train and use ML models. Next, you'll see how AutoML automates the entire process of training multiple models, optimizing their hyperparameters, as well as explaining their performance. As you advance, you'll find out how to leverage a Plain Old Java Object (POJO) and Model Object, Optimized (MOJO) to deploy your models to production. Throughout this book, you'll take a hands-on approach to implementation using H2O that'll enable you to set up your ML systems in no time. By the end of this H2O book, you'll be able to train and use your ML models using H2O AutoML, right from experimentation all the way to production without a single need to understand complex statistics or data science. What you will learnGet to grips with H2O AutoML and learn how to use itExplore the H2O Flow Web UIUnderstand how H2O AutoML trains the best models and automates hyperparameter optimizationFind out how H2O Explainability helps understand model performanceExplore H2O integration with scikit-learn, the Spring Framework, and Apache StormDiscover how to use H2O with Spark using H2O Sparkling WaterWho this book is for This book is for engineers and data scientists who want to quickly adopt machine learning into their products without worrying about the internal intricacies of training ML models. If you're someone who wants to incorporate machine learning into your software system but don't know where to start or don't have much expertise in the domain of ML, then you'll find this book useful. Basic knowledge of statistics and programming is beneficial. Some understanding of ML and Python will be helpful.
Practical Machine Learning with H2O by Darren Cook Pdf
Machine learning has finally come of age. With H2O software, you can perform machine learning and data analysis using a simple open source framework that’s easy to use, has a wide range of OS and language support, and scales for big data. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms. If you’re familiar with R or Python, know a bit of statistics, and have some experience manipulating data, author Darren Cook will take you through H2O basics and help you conduct machine-learning experiments on different sample data sets. You’ll explore several modern machine-learning techniques such as deep learning, random forests, unsupervised learning, and ensemble learning. Learn how to import, manipulate, and export data with H2O Explore key machine-learning concepts, such as cross-validation and validation data sets Work with three diverse data sets, including a regression, a multinomial classification, and a binomial classification Use H2O to analyze each sample data set with four supervised machine-learning algorithms Understand how cluster analysis and other unsupervised machine-learning algorithms work
In-situ H2O Removal Via Hydrophilic Membranes During Fischer-Tropsch and Other Fuel Related Synthesis Reactions by Martin Philipp Rohde Pdf
The general objective of this thesis was to explore the potential of in-situ H2O removal during fuel-related synthesis reactions with focus on in-situ H2O removal by hydrophilic membranes and by chemical reaction. It is demonstrated that in-situ H2O removal through vapour permeation during CO2 hydrogenation to Fischer-Tropsch hydrocarbons and during DME/DEE synthesis leads to increased conversion and yield levels, which are directly linked to the degree of H2O recovery.
Water and Life by Ruth M. Lynden-Bell,Simon Conway Morris,John D. Barrow,John L. Finney,Charles Harper Pdf
Reflecting a rich technical and interdisciplinary exchange of ideas, Water and Life: The Unique Properties of H20 focuses on the properties of water and its interaction with life. The book develops a variety of approaches that help to illuminate ways in which to address deeper questions with respect to the nature of the universe and our place within it. Grouped in five broad parts, this collection examines the arguments of Lawrence J. Henderson and other scholars on the "fitness" of water for life as part of the physical and chemical properties of nature considered as a foundational environment within which life has emerged and evolved. Leading authorities delve into a range of themes and questions that span key areas of ongoing debate and uncertainty. They draw from the fields of chemistry, biology, biochemistry, planetary and earth sciences, physics, astronomy, and their subspecialties. Several chapters also deal with humanistic disciplines, such as the history of science and theology, to provide additional perspectives. Bringing together highly esteemed researchers from multidisciplinary fields, this volume addresses fundamental questions relating to the possible role of water in the origin of life in the cosmos. It supports readers in their own explorations of the origin and meaning of life and the role of water in maintaining life.
When best friends, Cleo, Emma and Rikki find themselves accidentally stranded on a mysterious island something very strange happens. While swimming through an eerie underwater channel, the moon has a magical effect on the water changing the three girls forever. One by one the three friends discover that when they come into contact with water they grow a fishtail and become mermaids! Cleo, Emma and Rikki just want to be normal teenage girls and live normal lives, but as they start to come to terms with their new tails, not to mention their magical powers over H20, they begin to realise that they may never be normal again!
The brilliantly told and gripping story of the most familiar - yet, amazingly, still poorly understood - substance in the universe: Water. The extent to which water remains a scientific mystery is extraordinary, despite its prevalence and central importance on Earth. Whether one considers its role in biology, its place in the physical world (where it refuses to obey the usual rules of liquids) or its deceptively simple structure, there is still no complete answer to the question: what is water? Philip Ball's book explains what, exactly, we do and do not know about the strange character of this most essential and ubiquitous of substances. H20 begins by transporting its readers back to the Big Bang and the formation of galaxies to witness the birth of water's constituent elements: hydrogen and oxygen. It then explains how the primeval oceans were formed four billion years ago; where water is to be found on other planets; why ice floats when most solids sink; why, despite being highly corrosive, water is good for us; why there are at least fifteen kinds of ice and perhaps two kinds of liquid water; how scientists have consistently misunderstood water for centuries; and why wars have been waged over it. Philip Ball's gloriously offbeat and intelligent book conducts us on a journey through the history of science, folklore, the wilder scientific fringes, cutting-edge physics, biology and ecology, to give a fascinating new perspective on life and the substance that sustains it. After reading this book, drinking a glass of water will never be the same again.
This book is a unique synthesis of the latest findings in the quantum physics and chemistry of water that will tell you why it is so remarkably fit for life. It offers a novel panoramic perspective of cell biology based on water as "means, medium, and message" of life. This book is a sequel to The Rainbow and The Worm, The Physics of Organisms, which has remained in a class of its own for nearly 20 years since the publication of the first edition. Living Rainbow H2O continues the fascinating journey in the author's quest for the meaning of life, in science and beyond. Like The Rainbow and The Worm, the present book will appeal to readers in the arts and humanities as well as scientists; not least because the author herself is an occasional artist and poet. Great care has been taken to explain terms and concepts for the benefit of the general reader. At the same time, sufficient scientific details are provided in text boxes for the advanced reader and researcher without interrupting the main story.
Emma and Rikki love exploring their new mermaid powers. Cleo however, is not so sure. In fact, she'd do anything to give up her tail and become a normal girl again. But, aftr hearing rumours that sea turtles are becoming caught in fishermen's nets, Cleo begins to change her mind... Will Cleo learn to embrace her mermaid powers and use them to solve the mystery and help save the turtles?
