Download or read book L essentiel de l informatique en pr pa Exemples et exercices corrig s en SQL et Python written by Barrault Frantz and published by Editions Ellipses. This book was released on 2016-06-07 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: L’informatique est, depuis 2013, une discipline présente dans les programmes des classes préparatoires scientifiques. Cet ouvrage aborde de façon simple et efficace toutes les notions essentielles et nécessaires à la maîtrise de l’informatique au programme sans connaissances préalables. Ce livre s’adresse : • essentiellement aux élèves de première ou seconde année de CPGE scientifiques ; • aux futurs élèves de ces classes préparatoires qui désirent prendre de l’avance ; • à toute personne souhaitant acquérir des bases de la culture informatique et s’initier à la programmation dans les langages Python et SQL. Ce livre vous permettra : • d’apprendre de façon autonome à programmer en Python ou SQL grâce aux très nombreux exemples et schémas commentés ; • de vous exercer grâce aux exercices corrigés : des exercices d’application directe et d’autres plus élaborés concluent chaque chapitre ; • d’appréhender des notions plus complexes ou des problèmes en vue des concours (ou dans un objectif de pure curiosité). Afin, d’une part, de faciliter la compréhension des notions à ceux qui découvrent les langages de programmation et, d’autre part, de simplifier les révisions à ceux qui préparent des concours, un soin particulier a été apporté à la mise en page, aux graphiques, aux synthèses et à la présentation.

Download or read book L essentiel de l informatique en pr pa scientifique written by Frantz Barrault and published by Editions Ellipses. This book was released on 2021-10-12 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: À l’aide d’exemples commentés, de résumés, de QCM, d’exercices et de nombreux graphiques, ce livre propose les bases de l’informatique et celles de la programmation en Python, ainsi que de la notion d’algorithme. La dernière partie est une introduction aux bases de données et à leur manipulation grâce au langage SQL.

Download or read book L essentiel de l informatique en pr pa written by Frantz Barrault and published by . This book was released on 2016-06-07 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: L'informatique est, depuis 2013, une discipline présente dans les programmes des classes préparatoires scientifiques. Cet ouvrage aborde de façon simple et efficace toutes les notions essentielles et nécessaires à la maîtrise de l'informatique au programme sans connaissances préalables. Ce livre s'adresse : essentiellement aux élèves de première ou seconde année de CPGE scientifiques ; aux futurs élèves de ces classes préparatoires qui désirent prendre de l'avance ; à toute personne souhaitant acquérir des bases de la culture informatique et s'initier à la programmation dans les langages Python et SQL. Ce livre vous permettra : d'apprendre de façon autonome à programmer en Python ou SQL grâce aux très nombreux exemples et schémas commentés ; de vous exercer grâce aux exercices corrigés : des exercices d'application directe et d'autres plus élaborés concluent chaque chapitre ; d'appréhender des notions plus complexes ou des problèmes en vue des concours (ou dans un objectif de pure curiosité). Afin, d'une part, de faciliter la compréhension des notions à ceux qui découvrent les langages de programmation et, d'autre part, de simplifier les révisions à ceux qui préparent des concours, un soin particulier a été apporté à la mise en page, aux graphiques, aux synthèses et à la présentation.

Download or read book L essentiel de l informatique en pr pa scientifique written by Frantz Barrault and published by . This book was released on 2021-10-12 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Predicting Structured Data written by Neural Information Processing Systems Foundation and published by MIT Press. This book was released on 2007 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

Download or read book Informatique Pour Tous Programmation Python langage SQL CPGE scientifiques 1re et 2e ann es Fiches m thodes et exercices corrig s written by Canu Cécile and published by Editions Ellipses. This book was released on 2018-07-17 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Base de données utilisée dans les fiches 49 à 57 : world.db Image Lena512.bmp utilisé dans la fiche 26. Les ouvrages de cette collection ont pour objectif de faciliter l’acquisition et la maîtrise des notions fondamentales du programme. Le but est de faire en sorte que chacun sache « quoi faire », même lorsqu’il pense se trouver face à un obstacle insurmontable. Chaque fiche de ce livre est conçue de la façon suivante : - Quand on ne sait pas ! Les raisons expliquant pourquoi on ne sait pas, avec parfois des rappels de cours et les premières pistes à explorer afin de s’en sortir. - Que faire ? Les méthodes permettant de solutionner le type de problème étudié, assorties des rappels de cours essentiels à leur mise en oeuvre. - Conseils Les conseils de rédaction et une ou deux astuces pratiques. - Exemple traité Mise en pratique et en lumière de ce qui a été vu précédemment. - Exercices Énoncés choisis soigneusement afin de balayer largement le thème étudié, certains étant extraits de sujets de concours. - Pour vous aider à démarrer Les idées permettant de démarrer sereinement les exercices proposés. - Solutions des exercices Les solutions complètes et détaillées des exercices.

Download or read book Interactive Dashboards and Data Apps with Plotly and Dash written by Elias Dabbas and published by Packt Publishing Ltd. This book was released on 2021-05-21 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build web-based, mobile-friendly analytic apps and interactive dashboards with Python Key Features Develop data apps and dashboards without any knowledge of JavaScript Map different types of data such as integers, floats, and dates to bar charts, scatter plots, and more Create controls and visual elements with multiple inputs and outputs and add functionality to the app as per your requirements Book DescriptionPlotly's Dash framework is a life-saver for Python developers who want to develop complete data apps and interactive dashboards without JavaScript, but you'll need to have the right guide to make sure you’re getting the most of it. With the help of this book, you'll be able to explore the functionalities of Dash for visualizing data in different ways. Interactive Dashboards and Data Apps with Plotly and Dash will first give you an overview of the Dash ecosystem, its main packages, and the third-party packages crucial for structuring and building different parts of your apps. You'll learn how to create a basic Dash app and add different features to it. Next, you’ll integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app and then link them to charts and other outputs. Depending on the data you are visualizing, you'll also add several types of charts, including scatter plots, line plots, bar charts, histograms, and maps, as well as explore the options available for customizing them. By the end of this book, you'll have developed the skills you need to create and deploy an interactive dashboard, handle complexities and code refactoring, and understand the process of improving your application.What you will learn Find out how to run a fully interactive and easy-to-use app Convert your charts to various formats including images and HTML files Use Plotly Express and the grammar of graphics for easily mapping data to various visual attributes Create different chart types, such as bar charts, scatter plots, histograms, maps, and more Expand your app by creating dynamic pages that generate content based on URLs Implement new callbacks to manage charts based on URLs and vice versa Who this book is for This Plotly Dash book is for data professionals and data analysts who want to gain a better understanding of their data with the help of different visualizations and dashboards – and without having to use JS. Basic knowledge of the Python programming language and HTML will help you to grasp the concepts covered in this book more effectively, but it’s not a prerequisite.

Download or read book An Introduction to Computational Learning Theory written by Michael J. Kearns and published by MIT Press. This book was released on 1994-08-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.

Download or read book Machine Learning for Data Streams written by Albert Bifet and published by MIT Press. This book was released on 2018-03-16 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.

Download or read book The Nature of Statistical Learning Theory written by Vladimir Vapnik and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.

Download or read book Natural Language Processing with PyTorch written by Delip Rao and published by O'Reilly Media. This book was released on 2019-01-22 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems

Download or read book Elements of Causal Inference written by Jonas Peters and published by MIT Press. This book was released on 2017-11-29 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.

Download or read book Signal Processing for Communications written by Paolo Prandoni and published by Collection Savoir suisse. This book was released on 2008-06-17 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a novel, less classical approach to the subject, the authors have written a book with the conviction that signal processing should be taught to be fun. The treatment is therefore less focused on the mathematics and more on the conceptual aspects, the idea being to allow the readers to think about the subject at a higher conceptual level, thus building the foundations for more advanced topics. The book remains an engineering text, with the goal of helping students solve real-world problems. In this vein, the last chapter pulls together the individual topics as discussed throughout the book into an in-depth look at the development of an end-to-end communication system, namely, a modem for communicating digital information over an analog channel.

Download or read book Hands On Unsupervised Learning Using Python written by Ankur A. Patel and published by "O'Reilly Media, Inc.". This book was released on 2019-02-21 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied. Unsupervised learning, on the other hand, can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel shows you how to apply unsupervised learning using two simple, production-ready Python frameworks: Scikit-learn and TensorFlow using Keras. With code and hands-on examples, data scientists will identify difficult-to-find patterns in data and gain deeper business insight, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets. All you need is programming and some machine learning experience to get started. Compare the strengths and weaknesses of the different machine learning approaches: supervised, unsupervised, and reinforcement learning Set up and manage machine learning projects end-to-end Build an anomaly detection system to catch credit card fraud Clusters users into distinct and homogeneous groups Perform semisupervised learning Develop movie recommender systems using restricted Boltzmann machines Generate synthetic images using generative adversarial networks

Download or read book Toute l informatique en CPGE scientifiques 1re et 2e ann es Cours complet et d taill exercices corrig s avec Python SQL et Scilab annales corrig es written by Cochard Étienne, Rainero Sophie, Roussange Marielle, Sebert-Cuvillier Emmanuelle and published by Editions Ellipses. This book was released on 2016-01-26 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ce livre traite le programme d’informatique pour tous de classes préparatoires aux grandes écoles, première et seconde années, mais convient également à tout étudiant ou enseignant désireux de se former aux bases de la programmation en Python ou SQL (voire Scilab), ainsi qu’aux bases de l’ingénierie numérique (résolution approchée d’équations algébriques ou différentielles, calcul approché d’intégrales, etc.). Il propose un cours complet (incluant trois chapitres proposés comme thèmes d’étude dans le programme, dont les connaissances ne sont pas exigibles, mais peuvent aussi être utiles pour les travaux d’initiative personnelle encadrés (TIPE) et portant sur la programmation orientée objet, le traitement des images et la cryptographie), de très nombreux exercices corrigés, ainsi que les annales corrigées et commentées des épreuves écrites d’informatique de l’année 2015, y compris les parties d’informatique des sujets de mathématiques, physique ou sciences de l’ingénieur. Plusieurs documents annexes sont proposés au téléchargement (codes Python pour certains exercices, images, base de données à installer pour réaliser des tests, etc.) ; tous les sujets d’annales, à l’exception de quelques questions, sont accessibles dès la première année ; enfin un index complet permet de retrouver rapidement les réponses que l’on cherche.

Download or read book Reinforcement Learning second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

Download or read book Operations Research Introduction To Models And Methods written by Richard Johannes Boucherie and published by World Scientific. This book was released on 2021-10-26 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This attractive textbook with its easy-to-follow presentation provides a down-to-earth introduction to operations research for students in a wide range of fields such as engineering, business analytics, mathematics and statistics, computer science, and econometrics. It is the result of many years of teaching and collective feedback from students.The book covers the basic models in both deterministic and stochastic operations research and is a springboard to more specialized texts, either practical or theoretical. The emphasis is on useful models and interpreting the solutions in the context of concrete applications.The text is divided into several parts. The first three chapters deal exclusively with deterministic models, including linear programming with sensitivity analysis, integer programming and heuristics, and network analysis. The next three chapters primarily cover basic stochastic models and techniques, including decision trees, dynamic programming, optimal stopping, production planning, and inventory control. The final five chapters contain more advanced material, such as discrete-time and continuous-time Markov chains, Markov decision processes, queueing models, and discrete-event simulation.Each chapter contains numerous exercises, and a large selection of exercises includes solutions.