“…L’étude des représentations que l’on se fait des langues et de ceux qui les parlent se situe au carrefour de la linguistique et des autres disciplines des sciences sociales. En multipliant les points de vue et les angles d’attaque autour du concept d’imaginaire linguistique, le présent ouvrage, commis par des spécialistes en provenance de divers horizons disciplinaires, se veut une illustration du bon usage qui peut être fait de la pluridisciplinarité, de l’interdisciplinarité et de la transdisciplinarité…”

“…These ideas of eclectic approaches have been further developed (Hardingham, 2021; Passmore, 2021), with an emphasis on each coach developing their own distinctive evidenced-based approach informed by the cultural context, types of clients and their own personal style to build an approach which is informed by science but which can be flexed and adapted to meet the client where they are"--…”

“…Après avoir analysé le genre dissertatoire (notamment dans ses rapports controversés avec l’argumentation) et présenté quelques champs théoriques qui ont à faire avec l’exemple (de la rhétorique aristotélicienne aux sciences cognitives), l’ouvrage propose une théorie de l’exemplification comme opération discursive, en la spécifiant au niveau des organisations textuelles et de l’emploi de certains marqueurs (comme et par exemple). …”

“…Échappant un temps aux inventeurs, à l’Académie des sciences et au gouvernement, l’aérostation devient en France une invention partagée par de nombreux amateurs qui construisent un espace public de la technique dont l’expression culmine lors des envols. …”

“…Data/machine learning engineers and data scientists who build machine learning models for production systems in any domain, those supporting data engineers in productionizing ML models, and platform engineers who build data science (ML) platforms for the organization will also find plenty of practical advice in the later chapters of this book…”

“…A graduate of the McGill University School of Computer Science, he spent five years working for Microsoft, where he developed and managed developers on the Visual Basic, Visual J++, and .NET Windows Forms teams. …”

“…The final chapter relates to the rather onerous task of testing parallel and distributed applications, something that is not usually taught in standard computer science curricula. Style and approach Distributed Computing with Go takes you through a series of carefully graded tutorials, building ever more sophisticated applications…”

“…Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. …”

“…All of the Executive Briefings and detailed case studies from the exclusive AI Business Summit, including Kristian Hammond's (Northwestern Computer Science) day long tutorial offering a practical framework for bringing AI into your company; Adam Cheyer's (Samsung) look at how AI enables a totally new form of software development where humans and machines work collaboratively together; and Jennifer Fernick's (NCC Group) learned predictions of the industries that will benefit from the coming intersection of quantum computing, machine learning, and AI. …”

“…A graduate of the McGill University School of Computer Science, he spent five years working for Microsoft, where he developed and managed developers on the Visual Basic, Visual J++, and .NET Windows Forms teams. …”

“…Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of ..…”

“…What you will learn Prepare data for machine learning methods with ease Understand how to write production-ready code and package it for use Produce simple and effective data visualizations for improved insights Master advanced methods, such as Boosted Trees and deep neural networks Use natural language processing to extract insights in relation to text Implement tree-based classifiers, including Random Forest and Boosted Tree Who this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement..…”

“…What you will learn Set up a machine learning environment with Go libraries Use Gonum to perform regression and classification Explore time series models and decompose trends with Go libraries Clean up your Twitter timeline by clustering tweets Learn to use external services for your machine learning needs Recognize handwriting using neural networks and CNN with Gorgonia Implement facial recognition using GoCV and OpenCV Who this book is for If you're a machine learning engineer, data science professional, or Go programmer who wants to implement machine learning in your real-world projects and make smarter applications easily, this book is for you. …”

“…You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. …”

“…What you will learn Understand the Python data science stack and commonly used algorithms Build a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window Understand NLP concepts by creating a custom news feed Create applications that will recommend GitHub repositories based on ones you've starred, watched, or forked Gain the skills to build a chatbot from scratch using PySpark Develop a market-prediction app using stock data Delve into advanced concepts such as computer vision, neural networks, and deep learning Who this book is for This book is for machine learning practitioners, data scientists, and..…”

“…By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. …”

“…Studyopedia sells courses on Udemy, Tutorialspoint, Geeksforgeeks, and Skillshare, providing video courses to master various technologies and programming languages, databases, frameworks, Python, data science, machine learning, Java, Android, C/C++, HTML5, Bootstrap, JavaScript, jQuery, PHP, CSS, WordPress, Drupal, Joomla, Magento, osCommerce, OpenCart, PrestaShop, and other disciplines. …”

“…Studyopedia sells courses on Udemy, Tutorialspoint, Geeksforgeeks, and Skillshare, providing video courses to master various technologies and programming languages, databases, frameworks, Python, data science, machine learning, Java, Android, C/C++, HTML5, Bootstrap, JavaScript, jQuery, PHP, CSS, WordPress, Drupal, Joomla, Magento, osCommerce, OpenCart, PrestaShop, and other disciplines. …”

“…Challenges in Cybersecurity and Privacy - the European Research Landscape is ideal for personnel in computer/communication industries as well as academic staff and master/research students in computer science and communications networks interested in learning about cyber-security and privacy aspects…”

“…Rather than testing the content of learning, standards could relate to cognitive skills such as problem-solving, communicating and reasoning – with test/examination developers adapting those skills to subjects such as mathematics, science or literary analysis. Similarly, more use might be made of innovative assessment methods based on information and communication technologies, inasmuch as these may feature simulation or interactivity, for instance, at a reasonable cost. …”