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    • Logistic Regression

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    84 resultados referentes a "logistic regression"

    • Imperial College London

      Imperial College London

      Logistic Regression in R for Public Health

      Habilidades que você terá: Machine Learning Algorithms, Supply Chain, Machine Learning, Interpretation, General Statistics, Logistic Regression, Probability & Statistics, Regression, Bayesian Statistics

      4.8

      (316 avaliações)

      Intermediate · Course

    • Coursera Project Network

      Coursera Project Network

      Logistic Regression with NumPy and Python

      Habilidades que você terá: Statistical Programming, Machine Learning, Computer Programming, Supply Chain, Logistic Regression, Probability & Statistics

      4.5

      (385 avaliações)

      Beginner · Guided Project

    • SAS

      SAS

      Predictive Modeling with Logistic Regression using SAS

      Habilidades que você terá: Statistical Programming, Data Analysis, Computer Programming, Supply Chain, Business Analysis, Modeling, SAS (Software), Statistical Analysis, Probability & Statistics, Predictive Modelling, Python Programming

      4.6

      (31 avaliações)

      Intermediate · Course

    • Coursera Project Network

      Coursera Project Network

      Logistic Regression with Python and Numpy

      Habilidades que você terá: Theoretical Computer Science, Supply Chain, Logistic Regression, Numpy, Algorithms

      4.5

      (144 avaliações)

      Intermediate · Guided Project

    • Coursera Project Network

      Coursera Project Network

      Logistic Regression 101: US Household Income Classification

      Beginner · Guided Project

    • Coursera Project Network

      Coursera Project Network

      Predict Ad Clicks Using Logistic Regression and XG-Boost

      Beginner · Guided Project

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      Coursera Project Network

      Coursera Project Network

      Logistic Regression&application as Classification Algorithm

      Intermediate · Guided Project

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      Coursera Project Network

      Coursera Project Network

      Logistic Regression for Classification using Julia

      Habilidades que você terá: Probability & Statistics

      Beginner · Guided Project

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      DeepLearning.AI

      DeepLearning.AI

      Supervised Machine Learning: Regression and Classification

      Habilidades que você terá: Applied Machine Learning, Linear Algebra, Econometrics, Statistical Machine Learning, Machine Learning Algorithms, Theoretical Computer Science, Machine Learning, Mathematics, Logistic Regression, General Statistics, Feature Engineering, Probability & Statistics, Linear Regression, Linearity, Algorithms, Regression

      4.9

      (417 avaliações)

      Beginner · Course

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      DeepLearning.AI

      DeepLearning.AI

      Natural Language Processing

      Habilidades que você terá: Algorithms, Analysis, Artificial Neural Networks, Bayesian Statistics, Communication, Computer Graphics, Computer Programming, Deep Learning, Dimensionality Reduction, Experiment, General Statistics, Human Computer Interaction, Logistic Regression, Machine Learning, Machine Learning Algorithms, Markov Model, Mathematics, Natural Language, Natural Language Processing, Operations Research, Probability, Probability & Statistics, Process, Python Programming, Regression, Research and Design, Statistical Programming, Strategy and Operations, Theoretical Computer Science, User Experience

      4.6

      (4.5k avaliações)

      Intermediate · Specialization

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      IBM

      IBM

      IBM AI Engineering

      Habilidades que você terá: Algorithms, Apache, Applied Machine Learning, Artificial Neural Networks, Basic Descriptive Statistics, Big Data, Business Analysis, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Correlation And Dependence, Data Analysis, Data Management, Data Structures, Databases, Deep Learning, Dimensionality Reduction, Econometrics, General Statistics, Image Processing, Logistic Regression, Machine Learning, Machine Learning Algorithms, Mathematics, NoSQL, Probability & Statistics, Probability Distribution, Python Programming, Recommender Systems, Regression, SQL, Scikit-Learn, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Supply Chain Systems, Supply Chain and Logistics, Theoretical Computer Science

      4.6

      (14.6k avaliações)

      Intermediate · Professional Certificate

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      DeepLearning.AI

      DeepLearning.AI

      Neural Networks and Deep Learning

      Habilidades que você terá: General Statistics, Linear Algebra, Computer Programming, Machine Learning, Theoretical Computer Science, Supply Chain and Logistics, Machine Learning Algorithms, Business Psychology, Probability & Statistics, Applied Machine Learning, Mathematical Theory & Analysis, Entrepreneurship, Mathematics, Supply Chain, Hardware Design, Algorithms, Bayesian Statistics, Regression, Numpy, Computational Logic, Supply Chain Systems, Logistic Regression, Markov Model, Deep Learning, Artificial Neural Networks, Python Programming, Computer Architecture

      4.9

      (114.1k avaliações)

      Intermediate · Course

    Pesquisas relacionadas a logistic regression

    logistic regression with numpy and python
    logistic regression in r for public health
    logistic regression&application as classification algorithm
    logistic regression for classification using julia
    logistic regression with python and numpy
    logistic regression 101: us household income classification
    predictive modeling with logistic regression using sas
    predict ad clicks using logistic regression and xg-boost
    1234…7

    Em resumo, aqui estão 10 dos nossos cursos mais populares logistic regression

    • Logistic Regression in R for Public Health: Imperial College London
    • Logistic Regression with NumPy and Python: Coursera Project Network
    • Predictive Modeling with Logistic Regression using SAS: SAS
    • Logistic Regression with Python and Numpy: 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
    • Logistic Regression&application as Classification Algorithm: Coursera Project Network
    • Logistic Regression for Classification using Julia: Coursera Project Network
    • Supervised Machine Learning: Regression and Classification: DeepLearning.AI
    • Natural Language Processing: DeepLearning.AI

    Habilidades que você pode aprender em Probability And Statistics

    Linguagem R (19)
    Inferênciainferência (16)
    Regressão Linear (12)
    Análise Estatística (12)
    Inferência Estatística (11)
    Análise De Regressão (10)
    Bioestatísticabioestatísticas (9)
    Bayesiana (7)
    Distribuição De Probabilidade (7)
    Estatística Bayesiana (6)
    Estatísticas Médicas (6)

    Perguntas frequentes sobre Logistic Regression

    • 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.‎

    Este conteúdo de Perguntas frequentes foi disponibilizado apenas para fins informativos. Os aprendizes são aconselhados a realizar pesquisas adicionais para garantir que os cursos e outras credenciais buscadas atendam a seus objetivos pessoais, profissionais e financeiros.
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