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    • Logistic Regression

    筛选依据

    ''logistic regression'的 169 个结果

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      Imperial College London

      Logistic Regression in R for Public Health

      您将获得的技能: General Statistics, Machine Learning, Machine Learning Algorithms, Probability & Statistics, Regression, R Programming, Statistical Programming, Bayesian Statistics

      4.8

      (328 条评论)

      Intermediate · Course · 1-4 Weeks

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      SAS

      Predictive Modeling with Logistic Regression using SAS

      您将获得的技能: SAS (Software), Statistical Programming, Data Analysis, Data Mining, Machine Learning, Probability & Statistics, Regression, Statistical Analysis, Statistical Machine Learning, Exploratory Data Analysis, Machine Learning Algorithms, Statistical Tests, Advertising, Business Analysis, Computer Programming, General Statistics, Marketing, Python Programming

      4.6

      (42 条评论)

      Intermediate · Course · 1-3 Months

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      Coursera Project Network

      Logistic Regression with NumPy and Python

      您将获得的技能: Computer Programming, Machine Learning, Probability & Statistics, Statistical Programming, Data Science, Python Programming

      4.5

      (387 条评论)

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Logistic Regression for Classification using Julia

      您将获得的技能: Machine Learning, Probability & Statistics, Data Science

      3.7

      (7 条评论)

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Logistic Regression with Python and Numpy

      您将获得的技能: Algorithms, Machine Learning, Machine Learning Algorithms, Theoretical Computer Science, Communication, Deep Learning, Python Programming

      4.5

      (146 条评论)

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Logistic Regression&application as Classification Algorithm

      您将获得的技能: Data Analysis

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Logistic Regression 101: US Household Income Classification

      您将获得的技能: Machine Learning, Machine Learning Algorithms, Deep Learning, Python Programming

      4.8

      (6 条评论)

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Predict Ad Clicks Using Logistic Regression and XG-Boost

      您将获得的技能: Deep Learning, Machine Learning, Python Programming

      Beginner · Guided Project · Less Than 2 Hours

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      University of Chicago

      Machine Learning for Analytics MasterTrack™ Certificate

      您将获得的技能: Probability & Statistics, Machine Learning, General Statistics, Business Analysis, Data Analysis, Statistical Analysis, Experiment, Probability Distribution, Python Programming, Applied Machine Learning, Regression, Statistical Tests, Advertising, Algebra, Communication, Data Management, Data Structures, Linear Algebra, Machine Learning Algorithms, Marketing, Theoretical Computer Science

      提供的学分

      Mastertrack · 6-12 Months

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      Tufts University

      Business Analytics for Managers MasterTrack® Certificate

      您将获得的技能: Data Management, Financial Analysis

      提供的学分

      Mastertrack · 6-12 Months

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      Arizona State University

      AI and Machine Learning MasterTrack® Certificate

      您将获得的技能: Machine Learning, Theoretical Computer Science, Software Engineering, BlockChain, Finance, Software Architecture, Algorithms, Software Testing, Statistical Machine Learning, Computer Programming, Mobile Development, Deep Learning, Data Analysis, Computational Logic, Computer Architecture, Data Visualization, Databases, Mathematics, Probability & Statistics, Computational Thinking, Data Management, General Statistics, Mathematical Theory & Analysis, Programming Principles, Bayesian Network, Computer Vision, Data Mining, Data Structures, Design and Product, Distributed Computing Architecture, Feature Engineering, NoSQL, Operating Systems, Product Design, Security Engineering, Artificial Neural Networks, Operations Research, Probability Distribution, Research and Design, Strategy and Operations, Amazon Web Services, Application Development, Calculus, Cloud Computing, Communication, Cryptography, Data Model, Database Administration, Database Application, Database Design, Dimensionality Reduction, Hardware Design, Journalism, Microarchitecture, Mobile Security, SQL, Software Framework, Statistical Programming, System Programming, iOS Development, Advertising, Algebra, Computer Graphics, Computer Networking, Critical Thinking, Docker (Software), Econometrics, Entrepreneurship, Geovisualization, Human Computer Interaction, Leadership and Management, Marketing, Matlab, Network Security, Other Programming Languages, Planning, Python Programming, Scala Programming, Security Strategy, Spreadsheet Software, Statistical Tests, Supply Chain Systems, Supply Chain and Logistics, System Security, Tableau Software, User Experience, Web Development

      提供的学分

      Mastertrack · 6-12 Months

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      DeepLearning.AI,Stanford University

      Machine Learning

      您将获得的技能: Machine Learning, Probability & Statistics, Machine Learning Algorithms, General Statistics, Theoretical Computer Science, Algorithms, Applied Machine Learning, Artificial Neural Networks, Regression, Econometrics, Computer Programming, Deep Learning, Python Programming, Statistical Programming, Mathematics, Tensorflow, Data Management, Data Structures, Statistical Machine Learning, Reinforcement Learning, Probability Distribution, Mathematical Theory & Analysis, Data Analysis, Data Mining, Linear Algebra, Computer Vision, Calculus, Feature Engineering, Bayesian Statistics, Operations Research, Research and Design, Strategy and Operations, Computational Logic, Accounting, Communication

      4.9

      (7.9k 条评论)

      Beginner · Specialization · 1-3 Months

    与 logistic regression 相关的搜索

    logistic regression in r for public health
    logistic regression with python and numpy
    logistic regression 101: us household income classification
    logistic regression&application as classification algorithm
    logistic regression with numpy and python
    logistic regression for classification using julia
    predictive modeling with logistic regression using sas
    predict ad clicks using logistic regression and xg-boost
    1234…15

    总之,这是我们最受欢迎的 logistic regression 门课程中的 10 门

    • Logistic Regression in R for Public Health: Imperial College London
    • Predictive Modeling with Logistic Regression using SAS: SAS
    • Logistic Regression with NumPy and Python: Coursera Project Network
    • Logistic Regression for Classification using Julia: Coursera Project Network
    • Logistic Regression with Python and Numpy: Coursera Project Network
    • Logistic Regression&application as Classification Algorithm: Coursera Project Network
    • Logistic Regression 101: US Household Income Classification: Coursera Project Network
    • Predict Ad Clicks Using Logistic Regression and XG-Boost: Coursera Project Network
    • Machine Learning for Analytics MasterTrack™ Certificate: University of Chicago
    • Business Analytics for Managers MasterTrack® Certificate: Tufts University

    您可以在 Probability And Statistics 中学到的技能

    R 语言程序设计(中文版) (19)
    推断 (16)
    线性回归 (12)
    统计分析 (12)
    统计推断 (11)
    回归分析 (10)
    生物统计学 (9)
    贝叶斯定理 (7)
    概率分布 (7)
    贝叶斯统计 (6)
    医学统计 (6)

    关于 Logistic Regression 的常见问题

    • Logistic regression is a technique used in statistics that allows people to estimate the probability of something happening based on existing data they have about that event taking place before. Mathematical models are used often in science and engineering disciplines to explain concepts using mathematical language, and one of these models is logical regression. Logistic regression works using binary data, meaning there are only two possible outcomes for the event: It takes place, or it doesn’t take place. To figure out the probability of these two outcomes, logistic regression uses equations that calculate odds ratios — the odds that something will happen or it won’t. This predictive modeling tool plays a large role not only in statistics but also in machine learning, which involves computers learning information that they haven’t explicitly been programmed to process.‎

    • If you’re considering going into a career field that works with data, software or mathematics, logical regression is a valuable area of study to focus on. Logistic regression becomes an important step of the programming process when you’re building software that deals with predictive modeling or data analysis. And, if you’re interested in enhancing your understanding of machine learning, logistic regression is an essential. When you understand modeling with logical regression, you can progress more easily to the complex models involved with machine learning while learning how to best prepare data for processing.‎

    • A career as a data scientist or data analyst gives you the opportunity to apply your knowledge of logistic regression, but you’ll also frequently draw upon your skills in this arena if you want to go into the field of machine learning. Although these careers are relatively broad, working with machine learning and logistic regression is also possible in a variety of specialties you’ll find in software engineering, computational linguistics and software development. As you begin to learn more about logistic regression while taking online classes, you may discover a particular area of interest you want to explore — and your new skills can help you discover more.‎

    • Taking online courses about logistic regression can give you the knowledge you need to progress in your field or start fresh. In your career as a data scientist or analyst, you know the importance of statistical approaches and the variety of data-modeling techniques you utilize on a regular basis. But if you’re ready to dig deeper into these concepts to boost your understanding and put new ideas and skills into practice, taking online courses about logistic regression can get you where you want to go. If you’re starting with the basics, take a ground-up approach with introductory courses that create a solid foundation for future learning. Or, if you’re looking to supplement your existing knowledge base with a greater understanding of logistic regression, try courses that help you learn the concept’s role in machine learning and programming software for predictive modeling. You’ll appreciate your newfound comprehension of these innovative ideas — and you’ll love the freedom to participate in online courses when and where it’s most convenient for you.‎

    此常见问题解答内容仅供参考。建议学生多做研究,确保所追求的课程和其他证书符合他们的个人、专业和财务目标。
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