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Author: Ana Teresa Pérez-Leroux
Publisher: Cambridge University Press
ISBN: 1107018005
Category : Language Arts & Disciplines
Languages : en
Pages : 251
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Book Description
This book explores a much-debated area of language acquisition: the omission by young children of direct objects in a sentence.
Author: Ana Teresa Pérez-Leroux
Publisher: Cambridge University Press
ISBN: 1107018005
Category : Language Arts & Disciplines
Languages : en
Pages : 251
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Book Description
This book explores a much-debated area of language acquisition: the omission by young children of direct objects in a sentence.
Author: Anand Syea
Publisher: A&C Black
ISBN: 1441156380
Category : Language Arts & Disciplines
Languages : en
Pages : 321
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Book Description
A detailed study of different aspects of the syntax of Mauritian creole within a Chomksyan theoretical framework
Author: Stefanie Molin
Publisher: Packt Publishing Ltd
ISBN: 1789612802
Category : Computers
Languages : en
Pages : 702
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Book Description
Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery Key FeaturesPerform efficient data analysis and manipulation tasks using pandasApply pandas to different real-world domains using step-by-step demonstrationsGet accustomed to using pandas as an effective data exploration toolBook Description Data analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification, using scikit-learn, to make predictions based on past data. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. What you will learnUnderstand how data analysts and scientists gather and analyze dataPerform data analysis and data wrangling in PythonCombine, group, and aggregate data from multiple sourcesCreate data visualizations with pandas, matplotlib, and seabornApply machine learning (ML) algorithms to identify patterns and make predictionsUse Python data science libraries to analyze real-world datasetsUse pandas to solve common data representation and analysis problemsBuild Python scripts, modules, and packages for reusable analysis codeWho this book is for This book is for data analysts, data science beginners, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. You will also find this book useful if you are a data scientist who is looking to implement pandas in machine learning. Working knowledge of Python programming language will be beneficial.
Author: Kurt Braunmüller
Publisher: John Benjamins Publishing
ISBN: 9027273499
Category : Language Arts & Disciplines
Languages : en
Pages : 492
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Book Description
The 25 contributions of this volume represent a selection from the more than 120 papers originally presented at the International Conference on “Multilingual Individuals and Multilingual Societies” (MIMS), held in Hamburg (October 2010) and organized by the Collaborative Research Center “Multilingualism” after twelve years of successful research. It presents a panorama of contemporary research in multilingualism covering three fields of investigation: (1) the simultaneous and successive acquisition of more than one language, including language attrition in multilingual settings, (2) historical aspects of multilingualism and variance, and (3) multilingual communication. The papers cover a vast variety of linguistic phenomena including morphology, syntax, segmental and prosodic phonology as well as discourse production and language use, taking both individual and societal aspects of multilingualism into account. The languages addressed include numerous Romance, Slavic and Germanic varieties as well as Welsh, Hungarian, Turkish, and several South African autochthonous languages.
Author: Armin Schwegler
Publisher: John Benjamins Publishing
ISBN: 9027275696
Category : Language Arts & Disciplines
Languages : en
Pages : 359
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Book Description
This volume contains selected papers from the 27th Linguistic Symposium on Romance Languages (LSRL-27), which was held at the University of California, Irvine, on February 20-22, 1997. The 22 papers deal with current issues in linguistic theory as they can be illuminated by the close analysis and comparative study of Romance languages. A majority of the articles tackles topics in syntax and semantics; the rest is divided among topics in language acquisition, phonology, morphology, and sociolinguistics. Among the well-represented Romance languages examined are (Old) French, Italian, Spanish, and Portuguese.
Author: Teik Toe Teoh
Publisher: Springer Nature
ISBN: 9819945585
Category : Technology & Engineering
Languages : en
Pages : 385
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Book Description
Artificial intelligence (AI) is rapidly gaining significance in the business world. With more and more organizations adopt AI technologies, there is a growing demand for business leaders, managers, and practitioners who can harness AI’s potential to improve operations, increase efficiency, and drive innovation. This book aims to help management professionals exploit the predictive powers of AI and demonstrate to AI practitioners how to apply their expertise in fundamental business operations. It showcases how AI technology innovations can enhance various aspects of business management, such as business strategy, finance, and marketing. Readers interested in AI for business management will find several topics of particular interest, including how AI can improve decision-making in business strategy, streamline operational processes, and enhance customer satisfaction. As AI becomes an increasingly important tool in the business world, this book offers valuable insights into how it can be applied to various industries and business settings. Through this book, readers will gain a better understanding of how AI can be applied to improve business management practices and practical guidance on how to implement AI projects in a business context. This book also provides practical guides on how to implement AI projects in a business context using Python programming. By reading this book, readers will be better equipped to make informed decisions about how to leverage AI for business success.
Author: Wes McKinney
Publisher: "O'Reilly Media, Inc."
ISBN: 109810398X
Category : Computers
Languages : en
Pages : 609
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Book Description
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the Jupyter notebook and IPython shell for exploratory computing Learn basic and advanced features in NumPy Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Author: Eryk Lewinson
Publisher: Packt Publishing Ltd
ISBN: 1803238836
Category : Computers
Languages : en
Pages : 741
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Book Description
Use modern Python libraries such as pandas, NumPy, and scikit-learn and popular machine learning and deep learning methods to solve financial modeling problems Purchase of the print or Kindle book includes a free eBook in the PDF format Key FeaturesExplore unique recipes for financial data processing and analysis with PythonApply classical and machine learning approaches to financial time series analysisCalculate various technical analysis indicators and backtest trading strategiesBook Description Python is one of the most popular programming languages in the financial industry, with a huge collection of accompanying libraries. In this new edition of the Python for Finance Cookbook, you will explore classical quantitative finance approaches to data modeling, such as GARCH, CAPM, factor models, as well as modern machine learning and deep learning solutions. You will use popular Python libraries that, in a few lines of code, provide the means to quickly process, analyze, and draw conclusions from financial data. In this new edition, more emphasis was put on exploratory data analysis to help you visualize and better understand financial data. While doing so, you will also learn how to use Streamlit to create elegant, interactive web applications to present the results of technical analyses. Using the recipes in this book, you will become proficient in financial data analysis, be it for personal or professional projects. You will also understand which potential issues to expect with such analyses and, more importantly, how to overcome them. What you will learnPreprocess, analyze, and visualize financial dataExplore time series modeling with statistical (exponential smoothing, ARIMA) and machine learning modelsUncover advanced time series forecasting algorithms such as Meta's ProphetUse Monte Carlo simulations for derivatives valuation and risk assessmentExplore volatility modeling using univariate and multivariate GARCH modelsInvestigate various approaches to asset allocationLearn how to approach ML-projects using an example of default predictionExplore modern deep learning models such as Google's TabNet, Amazon's DeepAR and NeuralProphetWho this book is for This book is intended for financial analysts, data analysts and scientists, and Python developers with a familiarity with financial concepts. You'll learn how to correctly use advanced approaches for analysis, avoid potential pitfalls and common mistakes, and reach correct conclusions for a broad range of finance problems. Working knowledge of the Python programming language (particularly libraries such as pandas and NumPy) is necessary.
Author: Martin Fowler
Publisher: Addison-Wesley
ISBN: 013306526X
Category : Computers
Languages : en
Pages : 461
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Book Description
As the application of object technology--particularly the Java programming language--has become commonplace, a new problem has emerged to confront the software development community. Significant numbers of poorly designed programs have been created by less-experienced developers, resulting in applications that are inefficient and hard to maintain and extend. Increasingly, software system professionals are discovering just how difficult it is to work with these inherited, "non-optimal" applications. For several years, expert-level object programmers have employed a growing collection of techniques to improve the structural integrity and performance of such existing software programs. Referred to as "refactoring," these practices have remained in the domain of experts because no attempt has been made to transcribe the lore into a form that all developers could use. . .until now. In Refactoring: Improving the Design of Existing Code, renowned object technology mentor Martin Fowler breaks new ground, demystifying these master practices and demonstrating how software practitioners can realize the significant benefits of this new process. With proper training a skilled system designer can take a bad design and rework it into well-designed, robust code. In this book, Martin Fowler shows you where opportunities for refactoring typically can be found, and how to go about reworking a bad design into a good one. Each refactoring step is simple--seemingly too simple to be worth doing. Refactoring may involve moving a field from one class to another, or pulling some code out of a method to turn it into its own method, or even pushing some code up or down a hierarchy. While these individual steps may seem elementary, the cumulative effect of such small changes can radically improve the design. Refactoring is a proven way to prevent software decay. In addition to discussing the various techniques of refactoring, the author provides a detailed catalog of more than seventy proven refactorings with helpful pointers that teach you when to apply them; step-by-step instructions for applying each refactoring; and an example illustrating how the refactoring works. The illustrative examples are written in Java, but the ideas are applicable to any object-oriented programming language.
Author: Ana Teresa Pérez-Leroux
Publisher: Springer Science & Business Media
ISBN: 9401002916
Category : Language Arts & Disciplines
Languages : en
Pages : 286
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Book Description
Recent developments in linguistic theory, as well as the growing body of evidence from languages other than English, provide new opportunities for deeper explorations into how language is represented in the mind of learners. This collection of new empirical studies on the acquisition of Spanish morphosyntax by leading researchers in the field of language acquisition, specifically contributes to the characterization of the L1 / L2 connection in acquisition. Using L1 and L2 Spanish data from children and adults, the authors seek to address the central questions that have occupied developmental psycholinguists in the final decades of the previous century and that will no doubt continue engaging them into the present one.
