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Tag: machine learning: an applied mathematics introduction

  • The Modern Business Data Analyst: A Case Study Introduction into Business Data Analytics with CRISP-DM and R


    Price: $59.99
    (as of Jan 21,2025 20:29:55 UTC – Details)




    Publisher ‏ : ‎ Springer; 2024th edition (July 4, 2024)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 316 pages
    ISBN-10 ‏ : ‎ 3031599063
    ISBN-13 ‏ : ‎ 978-3031599064
    Item Weight ‏ : ‎ 1.21 pounds
    Dimensions ‏ : ‎ 7.01 x 0.72 x 10 inches


    In today’s fast-paced business environment, data analytics plays a crucial role in helping organizations make informed decisions and drive growth. As a modern business data analyst, it is essential to have a solid understanding of the tools and techniques used in data analysis.

    In this case study, we will explore the use of the CRoss-Industry Standard Process for Data Mining (CRISP-DM) methodology in business data analytics. CRISP-DM is a widely used framework for data mining and analytics projects, consisting of six phases: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment.

    We will also delve into the use of the R programming language, a powerful tool for data analysis and visualization. R is widely used in the industry for its flexibility, scalability, and extensive library of packages for statistical analysis and machine learning.

    Through this case study, we will demonstrate how a modern business data analyst can leverage CRISP-DM and R to extract valuable insights from data, build predictive models, and drive business decisions. Stay tuned for a deep dive into the world of business data analytics with CRISP-DM and R!
    #Modern #Business #Data #Analyst #Case #Study #Introduction #Business #Data #Analytics #CRISPDM,machine learning: an applied mathematics introduction

  • A Guide to R for Social and Behavioral Science Statistics


    Price: $78.99
    (as of Jan 21,2025 19:25:04 UTC – Details)




    Publisher ‏ : ‎ SAGE Publications, Inc; 1st edition (March 11, 2020)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 304 pages
    ISBN-10 ‏ : ‎ 1544344023
    ISBN-13 ‏ : ‎ 978-1544344027
    Item Weight ‏ : ‎ 1.1 pounds
    Dimensions ‏ : ‎ 7.38 x 0.69 x 9.13 inches


    R is a powerful statistical programming language that is widely used in social and behavioral science research. If you are new to R or looking to improve your skills, this guide is for you. Here are some key tips and resources to help you navigate R for social and behavioral science statistics:

    1. Learn the basics: Before diving into complex statistical analyses, it’s important to familiarize yourself with the basics of R programming. There are many online tutorials and courses available to help you get started.

    2. Understand data manipulation: Data manipulation is a key component of statistical analysis. In R, you can use packages like dplyr and tidyr to manipulate and clean your data before running statistical tests.

    3. Explore data visualization: Data visualization is an essential tool for understanding and communicating your findings. R offers a wide range of packages, such as ggplot2, for creating beautiful and informative visualizations.

    4. Master statistical analysis: R offers a wide range of statistical packages for conducting various analyses, such as regression, ANOVA, and factor analysis. Familiarize yourself with these packages to conduct robust statistical analyses.

    5. Seek help when needed: Don’t hesitate to ask for help when you encounter challenges with R. There are online communities, forums, and resources where you can seek assistance from experienced R users.

    By mastering R for social and behavioral science statistics, you can conduct rigorous and insightful research that contributes to the advancement of your field. Happy coding!
    #Guide #Social #Behavioral #Science #Statistics,machine learning: an applied mathematics introduction

  • An Introduction to Statistics and Data Analysis Using Stata®: From Research Design to Final Report


    Price: $142.00 – $96.33
    (as of Jan 21,2025 18:18:48 UTC – Details)




    Publisher ‏ : ‎ SAGE Publications, Inc; 1st edition (January 29, 2019)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 392 pages
    ISBN-10 ‏ : ‎ 1506371833
    ISBN-13 ‏ : ‎ 978-1506371832
    Item Weight ‏ : ‎ 1.42 pounds
    Dimensions ‏ : ‎ 7.38 x 0.89 x 9.13 inches


    Statistics and data analysis play a crucial role in research, providing valuable insights and guiding decision-making processes. Stata® is a powerful software tool that helps researchers analyze and interpret data effectively. In this post, we will provide an introduction to statistics and data analysis using Stata®, covering everything from research design to the final report.

    Research Design:
    Before diving into data analysis, it is essential to have a clear research design in place. This includes identifying the research question, selecting the appropriate data collection methods, and defining the variables of interest. A well-thought-out research design lays the foundation for a successful data analysis process.

    Data Collection:
    Once the research design is in place, data collection can begin. This may involve surveys, experiments, observations, or other methods of gathering data. It is crucial to ensure that the data collected is accurate, reliable, and relevant to the research question.

    Data Cleaning and Preparation:
    Before analyzing the data, it is important to clean and prepare it for analysis. This may involve checking for missing values, outliers, and inconsistencies in the data. Stata® offers a wide range of tools for data cleaning and manipulation, making it easier to prepare the data for analysis.

    Descriptive Statistics:
    Descriptive statistics provide a summary of the data, including measures of central tendency, dispersion, and distribution. Stata® offers a variety of commands for calculating descriptive statistics, such as mean, median, standard deviation, and histograms.

    Inferential Statistics:
    Inferential statistics allow researchers to draw conclusions and make predictions based on the data. This may involve hypothesis testing, regression analysis, or other statistical techniques. Stata® provides a comprehensive set of tools for conducting inferential statistics, making it easy to analyze complex data sets.

    Interpreting Results:
    Once the data analysis is complete, it is important to interpret the results and draw meaningful conclusions. Stata® offers various options for visualizing and presenting the results, such as graphs, tables, and statistical summaries. It is essential to communicate the findings clearly and accurately in the final report.

    In conclusion, statistics and data analysis are essential components of the research process, providing valuable insights and guiding decision-making. Stata® is a powerful software tool that helps researchers analyze and interpret data effectively. By following the steps outlined in this post, researchers can effectively use Stata® to analyze data from research design to the final report.
    #Introduction #Statistics #Data #Analysis #Stata #Research #Design #Final #Report,machine learning: an applied mathematics introduction

  • Data Science for Executives: Leveraging Machine Intelligence to Drive Business ROI


    Price: $19.99 – $17.99
    (as of Jan 21,2025 17:10:34 UTC – Details)




    Publisher ‏ : ‎ Lioncrest Publishing (October 12, 2018)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 266 pages
    ISBN-10 ‏ : ‎ 1544511256
    ISBN-13 ‏ : ‎ 978-1544511252
    Item Weight ‏ : ‎ 12 ounces
    Dimensions ‏ : ‎ 5.5 x 0.67 x 8.5 inches


    Data Science for Executives: Leveraging Machine Intelligence to Drive Business ROI

    In today’s data-driven world, executives are constantly looking for ways to stay ahead of the competition and drive business growth. One of the most powerful tools at their disposal is data science, a field that combines statistics, computer science, and domain expertise to extract valuable insights from large datasets.

    By harnessing the power of machine intelligence, executives can unlock the full potential of their data and drive significant return on investment (ROI) for their businesses. Machine learning algorithms can analyze vast amounts of data in real-time, identify patterns and trends, and make accurate predictions about future outcomes.

    From personalized marketing campaigns to predictive maintenance in manufacturing, the applications of data science are endless. Executives who understand how to leverage these technologies effectively can gain a competitive edge and drive innovation within their organizations.

    In this post, we will explore how executives can use data science to drive business ROI, including:

    – Identifying key business objectives and aligning data science initiatives with strategic goals
    – Building a data-driven culture within the organization and fostering collaboration between data scientists and business stakeholders
    – Implementing machine learning models to automate decision-making processes and optimize business operations
    – Measuring the impact of data science initiatives on key performance indicators and continuously refining strategies for maximum ROI

    By investing in data science and leveraging machine intelligence, executives can transform their businesses and stay ahead of the curve in today’s rapidly evolving marketplace. Stay tuned for more insights on how data science can drive business success and unlock new opportunities for growth.
    #Data #Science #Executives #Leveraging #Machine #Intelligence #Drive #Business #ROI,machine learning: an applied mathematics introduction

  • ggplot2: Elegant Graphics for Data Analysis (Use R!)


    Price: $47.49
    (as of Jan 21,2025 16:04:25 UTC – Details)




    ASIN ‏ : ‎ B00HWUXRP6
    Publisher ‏ : ‎ Springer; 1st ed. 2009. Corr. 3rd printing 2010 edition (October 3, 2009)
    Publication date ‏ : ‎ October 3, 2009
    Language ‏ : ‎ English
    File size ‏ : ‎ 11561 KB
    Text-to-Speech ‏ : ‎ Not enabled
    Enhanced typesetting ‏ : ‎ Not Enabled
    X-Ray ‏ : ‎ Not Enabled
    Word Wise ‏ : ‎ Not Enabled
    Print length ‏ : ‎ 213 pages
    Format ‏ : ‎ Print Replica

    Customers say

    Customers find the book a comprehensive resource for making innovative graphics. They appreciate its clear explanations of the underlying concepts and philosophy behind the ggplot2 library. The book provides excellent examples of ggplot code for graphical analysis. It is concise, well-written, and direct. Readers also mention that the images are beautiful and the graphs are flexible.

    AI-generated from the text of customer reviews


    Are you looking to create stunning and informative graphics for your data analysis projects? Look no further than ggplot2, a powerful package in R that allows you to create elegant and customizable graphics with ease.

    With ggplot2, you can easily produce beautiful and professional-looking plots for your data, whether you’re visualizing trends, relationships, distributions, or any other type of analysis. The package comes with a wide range of options for customizing your plots, including color schemes, themes, and annotations, allowing you to tailor your graphics to suit your needs.

    Whether you’re a beginner or an experienced R user, ggplot2 is a valuable tool that can help you take your data analysis to the next level. So why settle for dull and uninspiring graphics when you can create visually stunning and informative plots with ggplot2? Give it a try and see the difference it can make in your data analysis projects!
    #ggplot2 #Elegant #Graphics #Data #Analysis,machine learning: an applied mathematics introduction

  • Learning SAS by Example: A Programmer’s Guide


    Price: $89.95 – $52.19
    (as of Jan 21,2025 14:57:24 UTC – Details)




    Publisher ‏ : ‎ SAS Institute; 1st edition (March 26, 2007)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 664 pages
    ISBN-10 ‏ : ‎ 1599941651
    ISBN-13 ‏ : ‎ 978-1599941653
    Item Weight ‏ : ‎ 2.45 pounds
    Dimensions ‏ : ‎ 7.5 x 1.25 x 8.75 inches

    Customers say

    Customers find the book helpful for learning SAS. It provides simple examples and explanations that make learning easy. The exercises are well-chosen and provide programming solutions. Readers consider it a great value and a good purchase.

    AI-generated from the text of customer reviews


    Are you looking to enhance your SAS programming skills? Look no further! In this post, we will explore how to learn SAS through examples, providing a comprehensive guide for programmers of all levels.

    SAS (Statistical Analysis System) is a powerful software suite used for data management, analysis, and reporting. Whether you are a beginner or an experienced programmer, learning SAS by example can help you understand the language quickly and effectively.

    To start learning SAS, it is essential to familiarize yourself with the basic syntax and functions. By working through examples, you can see how different commands and procedures are used in real-world scenarios. This hands-on approach allows you to practice coding and gain a deeper understanding of SAS programming concepts.

    One of the best ways to learn SAS by example is to work on real datasets. By analyzing and manipulating data, you can see how different SAS procedures can be used to extract meaningful insights. Additionally, exploring case studies and practice exercises can help you apply your knowledge in practical situations.

    As you progress in your SAS learning journey, you can explore more advanced topics such as data visualization, statistical analysis, and macro programming. By continuously practicing and experimenting with different techniques, you can become proficient in SAS programming and unlock its full potential.

    In conclusion, learning SAS by example is a valuable approach for programmers looking to master the language. By working through hands-on exercises, analyzing real datasets, and exploring advanced topics, you can enhance your SAS skills and become a proficient programmer. So, what are you waiting for? Start learning SAS by example today and take your programming skills to the next level!
    #Learning #SAS #Programmers #Guide,machine learning: an applied mathematics introduction

  • Multilevel Analysis: An Introduction To Basic And Advanced Multilevel Modeling


    Price: $59.60
    (as of Jan 21,2025 13:52:19 UTC – Details)




    Publisher ‏ : ‎ SAGE Publications Ltd; Second edition (November 4, 2011)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 368 pages
    ISBN-10 ‏ : ‎ 184920201X
    ISBN-13 ‏ : ‎ 978-1849202015
    Item Weight ‏ : ‎ 1.36 pounds
    Dimensions ‏ : ‎ 6.69 x 0.83 x 9.53 inches


    Multilevel Analysis: An Introduction To Basic And Advanced Multilevel Modeling

    Multilevel analysis, also known as hierarchical linear modeling or mixed-effects modeling, is a powerful statistical technique used to analyze data that has a hierarchical or nested structure. This type of analysis is commonly used in social sciences, education, psychology, and other fields where data is collected at multiple levels of analysis.

    In this post, we will provide an overview of multilevel analysis, including the basic concepts and principles behind it, as well as an introduction to more advanced multilevel modeling techniques.

    At its core, multilevel analysis recognizes that data collected at different levels (e.g., individuals nested within groups) are not independent of each other and that this hierarchical structure must be taken into account when analyzing the data. By accounting for this nested structure, multilevel analysis allows researchers to more accurately estimate the effects of variables at different levels of analysis and to examine how these effects may vary across different levels.

    Basic multilevel modeling typically involves fitting a series of regression models at each level of analysis, with parameters representing the effects of variables at each level. More advanced multilevel modeling techniques, such as random effects models and growth curve modeling, allow for more complex and nuanced analyses of hierarchical data.

    Overall, multilevel analysis provides a powerful tool for researchers to better understand the complexities of data with hierarchical structures and to make more accurate and meaningful inferences about the relationships between variables at different levels of analysis.

    In future posts, we will delve deeper into specific multilevel modeling techniques and provide practical guidance on how to conduct multilevel analysis using statistical software such as R or SPSS. Stay tuned for more in-depth discussions on this important and versatile statistical methodology.
    #Multilevel #Analysis #Introduction #Basic #Advanced #Multilevel #Modeling,machine learning: an applied mathematics introduction

  • A First Course in Bayesian Statistical Methods (Springer Texts in Statistics)


    Price: $84.99 – $45.00
    (as of Jan 21,2025 12:44:01 UTC – Details)




    Publisher ‏ : ‎ Springer; 2009th edition (June 15, 2009)
    Language ‏ : ‎ English
    Hardcover ‏ : ‎ 280 pages
    ISBN-10 ‏ : ‎ 0387922997
    ISBN-13 ‏ : ‎ 978-0387922997
    Item Weight ‏ : ‎ 2.8 pounds
    Dimensions ‏ : ‎ 6.14 x 0.69 x 9.21 inches

    Customers say

    Customers find the book provides a good introduction to Bayesian analysis concepts with clear explanations and examples. They describe the content as excellent, thorough, and motivating. The R code provided is nice. However, some readers feel the book is not an easy introduction and not suitable for first-year courses. There are mixed opinions on the clarity of the text, with some finding it clear and easy to read, while others report errors and typos.

    AI-generated from the text of customer reviews


    Are you looking to dive into the world of Bayesian statistical methods? Look no further than “A First Course in Bayesian Statistical Methods” from the Springer Texts in Statistics series. This comprehensive and accessible textbook covers all the essential topics in Bayesian statistics, from basic concepts to advanced techniques.

    Whether you are a beginner or an experienced statistician, this book will provide you with a solid foundation in Bayesian methods. With clear explanations, numerous examples, and exercises to reinforce your understanding, this book is perfect for self-study or as a textbook for a course in Bayesian statistics.

    Don’t miss out on the opportunity to learn from one of the leading experts in the field. Get your copy of “A First Course in Bayesian Statistical Methods” today and start mastering Bayesian statistics!
    #Bayesian #Statistical #Methods #Springer #Texts #Statistics,machine learning: an applied mathematics introduction

  • Machine Learning And Its Applications



    Machine Learning And Its Applications

    Price : 224.49

    Ends on : N/A

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    Machine Learning And Its Applications

    Machine learning is a rapidly growing field within the realm of artificial intelligence that involves developing algorithms and models that allow computers to learn from and make predictions or decisions based on data. This technology has a wide range of applications across various industries, revolutionizing how businesses operate and how we interact with technology.

    One of the most well-known applications of machine learning is in the field of healthcare. Machine learning algorithms can be used to analyze medical images, such as X-rays and MRIs, to assist doctors in diagnosing diseases like cancer more accurately and quickly. Additionally, machine learning can be used to predict patient outcomes and recommend personalized treatment plans based on individual health data.

    In the financial sector, machine learning algorithms are used to detect fraudulent transactions, predict market trends, and optimize trading strategies. These algorithms can analyze vast amounts of financial data in real-time to make informed decisions and reduce risks for financial institutions.

    Machine learning also plays a crucial role in the field of marketing and advertising. Companies use machine learning algorithms to analyze customer behavior and preferences, personalize marketing campaigns, and recommend products or services to individual customers. This helps businesses improve customer engagement and increase sales.

    In the field of autonomous vehicles, machine learning algorithms are used to analyze sensory data from cameras, lidar, and radar to navigate and make decisions on the road. These algorithms enable vehicles to detect and respond to obstacles, traffic signs, and other vehicles in real-time, making autonomous driving safer and more reliable.

    Overall, machine learning has a diverse range of applications across various industries, from healthcare and finance to marketing and transportation. As technology continues to advance, we can expect to see even more innovative uses of machine learning that will continue to transform our world.
    #Machine #Learning #Applications,machine learning: an applied mathematics introduction

  • Machine Learning: A First Course for Engineers and Scientists by Lindholm



    Machine Learning: A First Course for Engineers and Scientists by Lindholm

    Price : 102.99

    Ends on : N/A

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    Machine Learning: A First Course for Engineers and Scientists by Lindholm

    Are you an engineer or scientist looking to delve into the world of machine learning? Look no further than “Machine Learning: A First Course” by Lindholm. This comprehensive guide is perfect for beginners who want to gain a solid understanding of the fundamental concepts and techniques behind machine learning.

    Lindholm takes a hands-on approach to teaching, providing practical examples and exercises to help you grasp complex topics. From regression analysis to neural networks, this book covers a wide range of machine learning algorithms and applications, making it an essential resource for anyone interested in this rapidly growing field.

    Whether you’re a student, researcher, or industry professional, “Machine Learning: A First Course” will equip you with the knowledge and skills you need to succeed in the world of machine learning. Pick up your copy today and start your journey towards mastering this exciting and in-demand technology.
    #Machine #Learning #Engineers #Scientists #Lindholm,machine learning: an applied mathematics introduction

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