Big Data et machine learning
Cet ouvrage s’adresse à tous ceux qui réfléchissent à la meilleure utilisation possible des données au sein de l’entreprise, qu’ils soient data scientists, DSI, chefs de projets ou spécialistes métier. Le Big Data s’est imposé comme une innovation majeure pour toutes les entreprises qui cherchent à construire un avantage concurrentiel grâce à l’exploitation de leurs données clients, fournisseurs, produits, processus, machines, etc. Mais quelle solution technique choisir ? Quelles compétences métier développer au sein de la DSI ? Ce livre est un guide pour comprendre les enjeux d’un projet Big Data, en appréhender les concepts sous-jacents (en particulier le machine learning) et acquérir les compétences nécessaires à la mise en place d’un data lab. Il combine la présentation : • de notions théoriques (traitement statistique des données, calcul distribué...) ; • d’outils (écosystème Hadoop, Storm...) ; • d’exemples de machine learning ; • d’une organisation typique d’un projet de data science.
Use the functionalities of Kibana to discover data and build attractive visualizations and dashboards for real-world scenarios About This Book Perform real-time data analytics and visualizations, on streaming data, using Kibana Build beautiful visualizations and dashboards with simplicity and ease without any type of coding involved Learn all the core concepts as well as detailed information about each component used in Kibana Who This Book Is For Whether you are new to the world of data analytics and data visualization or an expert, this book will provide you with the skills required to use Kibana with ease and simplicity for real-time data visualization of streaming data. This book is intended for those professionals who are interested in learning about Kibana,its installations, and how to use it . As Kibana provides a user-friendly web page, no prior experience is required. What You Will Learn Understand the basic concepts of elasticsearch used in Kibana along with step by step guide to install Kibana in Windows and Ubuntu Explore the functionality of all the components used in Kibana in detail, such as the Discover, Visualize, Dashboard,and Settings pages Analyze data using the powerful search capabilities of elasticsearch Understand the different types of aggregations used in Kibana for visualization Create and build different types of amazing visualizations and dashboards easily Create, save, share, embed, and customize the visualizations added to the dashboard Customize and tweak the advanced settings of Kibana to ensure ease of use In Detail With the increasing interest in data analytics and visualization of large data around the globe, Kibana offers the best features to analyze data and create attractive visualizations and dashboards through simple-to-use web pages. The variety of visualizations provided, combined with the powerful underlying elasticsearch capabilities will help professionals improve their skills with this technology. This book will help you quickly familiarize yourself to Kibana and will also help you to understand the core concepts of this technology to build visualizations easily. Starting with setting up of Kibana and elasticsearch in Windows and Ubuntu, you will then use the Discover page to analyse your data intelligently. Next, you will learn to use the Visualization page to create beautiful visualizations without the need for any coding. Then, you will learn how to use the Dashboard page to create a dashboard and instantly share and embed the dashboards. You will see how to tweak the basic and advanced settings provided in Kibana to manage searches, visualizations, and dashboards. Finally, you will use Kibana to build visualizations and dashboards for real-world scenarios. You will quickly master the functionalities and components used in Kibana to create amazing visualizations based on real-world scenarios. With ample screenshots to guide you through every step, this book will assist you in creating beautiful visualizations with ease. Style and approach This book is a comprehensive step-by-step guide to help you understand Kibana. It's explained in an easy-to-follow style along with supporting images. Every chapter is explained sequentially , covering the basics of each component of Kibana and providing detailed explanations of all the functionalities of Kibana that appeal.
Real World OCaml
This fast-moving tutorial introduces you to OCaml, an industrial-strength programming language designed for expressiveness, safety, and speed. Through the book’s many examples, you’ll quickly learn how OCaml stands out as a tool for writing fast, succinct, and readable systems code. Real World OCaml takes you through the concepts of the language at a brisk pace, and then helps you explore the tools and techniques that make OCaml an effective and practical tool. In the book’s third section, you’ll delve deep into the details of the compiler toolchain and OCaml’s simple and efficient runtime system. Learn the foundations of the language, such as higher-order functions, algebraic data types, and modules Explore advanced features such as functors, first-class modules, and objects Leverage Core, a comprehensive general-purpose standard library for OCaml Design effective and reusable libraries, making the most of OCaml’s approach to abstraction and modularity Tackle practical programming problems from command-line parsing to asynchronous network programming Examine profiling and interactive debugging techniques with tools such as GNU gdb
Managing Complexity of Information Systems
This book is about complexity in Information Systems (IS). The subject is addressed from both conceptual and applied perspectives. Concepts are drawn from information theory, industrial design and software engineering. Its content capitalizes on experiences gathered by the authors during various contracting jobs involving software architecture, modeling and IS architecture that were conducted for large organizations in the banking and industry sectors, as well as in the public sector. The authors develop the point of view according to which mastering complexity involves two essential steps: first, one should develop a clear understanding of the real nature of complexity within the IS; second, one should identify the primary causes which contribute to its uncontrolled growth and organize these into a logical framework, in order to define efficient countermeasures. Both technical and psychological causes of complexity are to be considered. Two themes make up the main thread of the book: complexity and value. Both themes are quite common when considered separately, but their interplay remains a largely unexplored topic. The analysis of this interplay is one of the sources of originality of this book.
The Lean Mindset
What company doesn’t want energized workers, delighted customers, genuine efficiency, and breakthrough innovation? The Lean Mindset shows how lean companies really work–and how a lean mindset is the key to creating stunning products and delivering amazing services. Through cutting-edge research and case studies from leading organizations, including Spotify, Ericsson, Intuit, GE Healthcare, Pixar, CareerBuilder, and Intel, you’ll discover proven patterns for developing that mindset. You’ll see how to cultivate product teams that act like successful startups, create the kind of efficiency that attracts customers, and leverage the talents of bright, creative people. The Poppendiecks weave lean principles throughout this book, just as those principles must be woven throughout the fabric of your truly lean organization. Learn How To Start with an inspiring purpose, and overcome the curse of short-term thinking Energize teams by providing well-framed challenges, larger purposes, and a direct line of sight between their work and the achievement of those purposes Delight customers by gaining unprecedented insight into their real needs, and building products and services that fully anticipate those needs Achieve authentic, sustainable efficiency without layoffs, rock-bottom cost focus, or totalitarian work systems Develop breakthrough innovations by moving beyond predictability to experimentation, beyond globalization to decentralization, beyond productivity to impact Lean approaches to software development have moved from novelty to widespread use, in large part due to the principles taught by Mary and Tom Poppendieck in their pioneering books. Now, in The Lean Mindset, the Poppendiecks take the next step, looking at a company where multidiscipline teams are expected to ask the right questions, solve the right problems, and deliver solutions that customers love.
Probabilistic Reasoning in Intelligent Systems
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
Approaches to Legal Ontologies
The book provides the reader with a unique source regarding the current theoretical landscape in legal ontology engineering as well as on foreseeable future trends for the definition of conceptual structures to enhance the automatic processing and retrieval of legal information in the Semantic Web framework. It will thus interest researchers in the domains of the SW, legal informatics, Artificial Intelligence and law, legal theory and legal philosophy, as well as developers of e-government applications based on the intelligent management of legal or public information to provide both back-office and front-office support.
Machine Learning with Spark
If you are a Scala, Java, or Python developer with an interest in machine learning and data analysis and are eager to learn how to apply common machine learning techniques at scale using the Spark framework, this is the book for you. While it may be useful to have a basic understanding of Spark, no previous experience is required.
Agricultural Innovation Systems
Managing the ability of agriculture to meet rising global demand and to respond to the changes and opportunities will require good policy, sustained investments, and innovation - not business as usual. Investments in public Research and Development, extension, education, and their links with one another have elicited high returns and pro-poor growth, but these investments alone will not elicit innovation at the pace or on the scale required by the intensifying and proliferating challenges confronting agriculture. Experience indicates that aside from a strong capacity in Research and Development, the ability to innovate is often related to collective action, coordination, the exchange of knowledge among diverse actors, the incentives and resources available to form partnerships and develop businesses, and conditions that make it possible for farmers or entrepreneurs to use the innovations. While consensus is developing about what is meant by 'innovation' and 'innovation system', no detailed blueprint exists for making agricultural innovation happen at a given time, in a given place, for a given result. The AIS approach that looks at these multiple conditions and relationships that promote innovation in agriculture, has however moved from a concept to a sub-discipline with principles of analysis and action. AIS investments must be specific to the context, responding to the stage of development in a particular country and agricultural sector, especially the AIS. This sourcebook contributes to identifying, designing, and implementing the investments, approaches, and complementary interventions that appear most likely to strengthen AIS and to promote agricultural innovation and equitable growth. It emphasizes the lessons learned, benefits and impacts, implementation issues, and prospects for replicating or expanding successful practices. The information in this sourcebook derives from approaches that have been tested at different scales in different contexts. It reflects the experiences and evolving understanding of numerous individuals and organizations concerned with agricultural innovation, including the World Bank. This information is targeted to the key operational staff in international and regional development agencies and national governments who design and implement lending projects and to the practitioners who design thematic programs and technical assistance packages. The sourcebook can also be an important resource for the research community and nongovernmental organizations (NGOs).