Search results for: the-hundred-page-machine-learning-book

The Hundred page Machine Learning Book

Author : Andriy Burkov
File Size : 22.61 MB
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Endorsed by top AI authors, academics and industry leaders, The Hundred-Page Machine Learning Book is the number one bestseller on Amazon and the most recommended book for starters and experienced professionals alike.

The Hundred page Machine Learning Book en Fran ais

Author : Andriy Burkov
File Size : 54.22 MB
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"Le livre d'Andriy Burkov suit la même philosophie. Il évite les détails trop théoriques, au profit des conseils techniques concernant l'implémentation pratique des approches présentées. C'est un guide compact de la "science des données appliquée" et je prédis qu'il va devenir une ressource de référence pour les universitaires et les praticiens. Avec 100 pages (ou un petit peu plus), ce livre est suffisamment court pour être lu d'une traite. Cependant, ne vous y fiez pas : il couvre toute les principales approches de l'apprentissage machine, allant des classiques régressions linéaire et logistique, en passant par les méthodes les plus modernes comme les séparateurs à vaste marge, l'apprentissage profond, le boosting et les forêts aléatoires."--Avant-propos de l'édition anglaise.

Neuronale Netze Selbst Programmieren

Author : Tariq Rashid
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Neuronale Netze sind Schlüsselelemente des Deep Learning und der Künstlichen Intelligenz, die heute zu Erstaunlichem in der Lage sind. Dennoch verstehen nur wenige, wie Neuronale Netze tatsächlich funktionieren. Dieses Buch nimmt Sie mit auf eine unterhaltsame Reise, die mit ganz einfachen Ideen beginnt und Ihnen Schritt für Schritt zeigt, wie Neuronale Netze arbeiten. Dafür brauchen Sie keine tieferen Mathematik-Kenntnisse, denn alle mathematischen Konzepte werden behutsam und mit vielen Illustrationen erläutert. Dann geht es in die Praxis: Sie programmieren Ihr eigenes Neuronales Netz mit Python und bringen ihm bei, handgeschriebene Zahlen zu erkennen, bis es eine Performance wie ein professionell entwickeltes Netz erreicht. Zum Schluss lassen Sie das Netz noch auf einem Raspberry Pi Zero laufen. - Tariq Rashid hat eine besondere Fähigkeit, schwierige Konzepte verständlich zu erklären, dadurch werden Neuronale Netze für jeden Interessierten zugänglich und praktisch nachvollziehbar.

Machine Learning Engineering

Author : Andriy Burkov
File Size : 23.32 MB
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From the author of a world bestseller published in eleven languages, The Hundred-Page Machine Learning Book, this new book by Andriy Burkov is the most complete applied AI book out there. It is filled with best practices and design patterns of building reliable machine learning solutions that scale. Andriy Burkov has a Ph.D. in AI and is the leader of a machine learning team at Gartner. This book is based on Andriy's own 15 years of experience in solving problems with AI as well as on the published experience of the industry leaders. "If you intend to use machine learning to solve business problems at scale, I'm delighted you got your hands on this book." -Cassie Kozyrkov, Chief Decision Scientist at Google "Foundational work about the reality of building machine learning models in production." -Karolis Urbonas, Head of Machine Learning and Science at Amazon

Hands On Machine Learning with Scikit Learn Keras and TensorFlow

Author : Aurélien Géron
File Size : 37.1 MB
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Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets

Hands On Python Deep Learning for the Web

Author : Anubhav Singh
File Size : 67.63 MB
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Use the power of deep learning with Python to build and deploy intelligent web applications Key Features Create next-generation intelligent web applications using Python libraries such as Flask and Django Implement deep learning algorithms and techniques for performing smart web automation Integrate neural network architectures to create powerful full-stack web applications Book Description When used effectively, deep learning techniques can help you develop intelligent web apps. In this book, you'll cover the latest tools and technological practices that are being used to implement deep learning in web development using Python. Starting with the fundamentals of machine learning, you'll focus on DL and the basics of neural networks, including common variants such as convolutional neural networks (CNNs). You'll learn how to integrate them into websites with the frontends of different standard web tech stacks. The book then helps you gain practical experience of developing a deep learning-enabled web app using Python libraries such as Django and Flask by creating RESTful APIs for custom models. Later, you'll explore how to set up a cloud environment for deep learning-based web deployments on Google Cloud and Amazon Web Services (AWS). Next, you'll learn how to use Microsoft's intelligent Emotion API, which can detect a person's emotions through a picture of their face. You'll also get to grips with deploying real-world websites, in addition to learning how to secure websites using reCAPTCHA and Cloudflare. Finally, you'll use NLP to integrate a voice UX through Dialogflow on your web pages. By the end of this book, you'll have learned how to deploy intelligent web apps and websites with the help of effective tools and practices. What you will learn Explore deep learning models and implement them in your browser Design a smart web-based client using Django and Flask Work with different Python-based APIs for performing deep learning tasks Implement popular neural network models with TensorFlow.js Design and build deep web services on the cloud using deep learning Get familiar with the standard workflow of taking deep learning models into production Who this book is for This deep learning book is for data scientists, machine learning practitioners, and deep learning engineers who are looking to perform deep learning techniques and methodologies on the web. You will also find this book useful if you’re a web developer who wants to implement smart techniques in the browser to make it more interactive. Working knowledge of the Python programming language and basic machine learning techniques will be beneficial.

Industry 4 0 Interoperability Analytics Security and Case Studies

Author : G. Rajesh
File Size : 42.60 MB
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All over the world, vast research is in progress on the domain of Industry 4.0 and related techniques. Industry 4.0 is expected to have a very high impact on labor markets, global value chains, education, health, environment, and many social economic aspects. Industry 4.0 Interoperability, Analytics, Security, and Case Studies provides a deeper understanding of the drivers and enablers of Industry 4.0. It includes real case studies of various applications related to different fields, such as cyber physical systems (CPS), Internet of Things (IoT), cloud computing, machine learning, virtualization, decentralization, blockchain, fog computing, and many other related areas. Also discussed are interoperability, design, and implementation challenges. Researchers, academicians, and those working in industry around the globe will find this book of interest. FEATURES Provides an understanding of the drivers and enablers of Industry 4.0 Includes real case studies of various applications for different fields Discusses technologies such as cyber physical systems (CPS), Internet of Things (IoT), cloud computing, machine learning, virtualization, decentralization, blockchain, fog computing, and many other related areas Covers design, implementation challenges, and interoperability Offers detailed knowledge on Industry 4.0 and its underlying technologies, research challenges, solutions, and case studies

10th International Conference on Theory and Application of Soft Computing Computing with Words and Perceptions ICSCCW 2019

Author : Rafik A. Aliev
File Size : 66.48 MB
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This book presents the proceedings of the 10th Conference on Theory and Applications of Soft Computing, Computing with Words and Perceptions, ICSCCW 2019, held in Prague, Czech Republic, on August 27–28, 2019. It includes contributions from diverse areas of soft computing and computing with words, such as uncertain computation, decision-making under imperfect information, neuro-fuzzy approaches, deep learning, natural language processing, and others. The topics of the papers include theory and applications of soft computing, information granulation, computing with words, computing with perceptions, image processing with soft computing, probabilistic reasoning, intelligent control, machine learning, fuzzy logic in data analytics and data mining, evolutionary computing, chaotic systems, soft computing in business, economics and finance, fuzzy logic and soft computing in earth sciences, fuzzy logic and soft computing in engineering, fuzzy logic and soft computing in material sciences, soft computing in medicine, biomedical engineering, and pharmaceutical sciences. Showcasing new ideas in the field of theories of soft computing and computing with words and their applications in economics, business, industry, education, medicine, earth sciences, and other fields, it promotes the development and implementation of these paradigms in various real-world contexts. This book is a useful guide for academics, practitioners and graduates.

Williams Hematology 10th Edition

Author : Kenneth Kaushansky
File Size : 57.43 MB
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The landmark text that has guided generations of hematologists and related practitioners―updated with the latest research findings and improved format and presentation Long revered for its comprehensiveness and extraordinary depth of detail, Williams Hematology provides essential coverage of the origins, pathophysiological mechanisms, and management of benign and malignant disorders of blood and marrow cells and coagulation proteins. The text contains a wealth of basic science and translational pathophysiology for optimal, lifelong learning. Experts in research and clinical hematology, the editors are known worldwide for their contributions to the field. This new edition contains everything that has made Williams Hematology the go-to resource for decades and has been updated with new chapters and critical new research into the molecular mechanisms responsible for hematological disorders and the impact on diagnosis and treatment. And the new format enables you to access each chapter via content modules covering key topics, with summaries, infographics, and cases―all linked to review questions for self-assessment. The full-color presentation integrates images of blood and tissue findings where they are cited in the text. NEW TO THIS EDITION: Updated and revised content reflecting the latest research and developments Convenient format that streamlines the learning process and improves retention Additional chapters added on: Immune Checkpoint Inhibitors Immune Cell Therapy: Chimeric Antigen Receptor T Cell Therapy Immune Cell Therapy Dendritic Cell and Natural Killer Cell Therapy The processes of cell death and survival Application of Big Data and Deep Learning in Hematology Williams Hematology Cases with multiple-choice questions including detailed explanations—perfect preparation for the boards Continuously updated online content with comprehensive drug therapy database and other resources

Indiana Medical Journal

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File Size : 41.65 MB
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The Outlook

Author :
File Size : 74.94 MB
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Learning from Data

Author : Vladimir Cherkassky
File Size : 84.90 MB
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An interdisciplinary framework for learning methodologies—covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied—showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.

The Critic

Author : Jeannette Leonard Gilder
File Size : 63.71 MB
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Book Review Digest

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The Saturday Review of Politics Literature Science and Art

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File Size : 90.56 MB
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A Global Approach to Data Value Maximization

Author : Paolo Dell’Aversana
File Size : 27.2 MB
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This book presents a systematic discussion about methods and techniques used to extract the maximum informative value from complex data sets. A multitude of approaches and techniques can be applied for that purpose, including data fusion and model integration, multimodal data analysis in different physical domains, audio-video display of data through techniques of “sonification”, multimedia machine learning, and hybrid methods of data analysis. The book begins with the domain of geosciences, before moving on to other scientific areas, like diagnostic medicine and various engineering sectors. As such, it will appeal to a large audience, including geologists and geophysicists, data scientists, physicians and cognitive scientists, and experts in social sciences and knowledge management.

Scott Browne s Text book of Phonography

Author : D. L. Scott-Browne
File Size : 88.83 MB
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Paperbound Books in Print

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File Size : 39.15 MB
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Roadside Video Data Analysis

Author : Brijesh Verma
File Size : 39.69 MB
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This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.

The Accountant

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File Size : 59.90 MB
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