Math for Machine Learning

Math for Machine Learning

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Learn the core topics of Machine Learning to open doors to data science and artificial intelligence. If you're looking to gain a solid foundation in Machine Learning, allowing you to study on your own schedule at a fraction of the cost it would take at a traditional university, to further your career goals, this online course is for you. Practice problems available at onlinemathtraining.
20181 σεζόν
Ειδικού ενδιαφέροντος
Ειδικού ενδιαφέροντος
20181 σεζόν
Ηθοποιοί: Richard Han
ΌΛΑ
Σεζόν 1
72 επεισόδια

  • 1. Introduction Lecture (1 of 72 Lectures)

    1. Introduction Lecture (1 of 72 Lectures)

    An introduction to the course is provided. Practice problems available at onlinemathtraining.
    An introduction to the course is provided. Practice problems available at onlinemathtraining.
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    3 λεπτά
    2 Μαΐ 2018
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  • 2. Section 1: Linear Regression (First Lecture: Linear Regression)

    2. Section 1: Linear Regression (First Lecture: Linear Regression)

    Students will learn about the notion of residual sum of squares. Practice problems available at onlinemathtraining.
    Students will learn about the notion of residual sum of squares. Practice problems available at onlinemathtraining.
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    8 λεπτά
    2 Μαΐ 2018
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  • 3. The Least Squares Method

    3. The Least Squares Method

    Students will learn how to apply the least squares method to solve the least squares problem.
    Students will learn how to apply the least squares method to solve the least squares problem.
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    11 λεπτά
    2 Μαΐ 2018
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  • 4. Linear Algebra Solution to Least Squares Problem

    4. Linear Algebra Solution to Least Squares Problem

    Students will learn about a linear algebra approach to solving the least squares problem.
    Students will learn about a linear algebra approach to solving the least squares problem.
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    13 λεπτά
    2 Μαΐ 2018
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  • 5. Example: Linear Regression

    5. Example: Linear Regression

    An example of applying the least squares method is provided.
    An example of applying the least squares method is provided.
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    4 λεπτά
    2 Μαΐ 2018
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  • 6. Summary: Linear Regression

    6. Summary: Linear Regression

    A summary of linear regression is provided.
    A summary of linear regression is provided.
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    34 δευτ.
    2 Μαΐ 2018
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  • 7. Section 2: Linear Discriminant Analysis (First Lecture: Classification)

    7. Section 2: Linear Discriminant Analysis (First Lecture: Classification)

    Students will be introduced to classification problems. Practice problems available at onlinemathtraining.
    Students will be introduced to classification problems. Practice problems available at onlinemathtraining.
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    1 λεπτά
    2 Μαΐ 2018
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  • 8. Linear Discriminant Analysis

    8. Linear Discriminant Analysis

    The method of linear discriminant analysis is introduced.
    The method of linear discriminant analysis is introduced.
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    44 δευτ.
    2 Μαΐ 2018
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  • 9. The Posterior Probability Functions

    9. The Posterior Probability Functions

    In this lecture, we build a formula for the posterior probability.
    In this lecture, we build a formula for the posterior probability.
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    4 λεπτά
    2 Μαΐ 2018
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  • 10. Modelling the Posterior Probability Functions

    10. Modelling the Posterior Probability Functions

    In this lecture, we model the posterior probability functions.
    In this lecture, we model the posterior probability functions.
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    7 λεπτά
    2 Μαΐ 2018
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  • 11. Linear Discriminant Functions

    11. Linear Discriminant Functions

    Students will learn what linear discriminant functions are.
    Students will learn what linear discriminant functions are.
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    6 λεπτά
    2 Μαΐ 2018
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  • 12. Estimating the Linear Discriminant Functions

    12. Estimating the Linear Discriminant Functions

    In this lecture, we estimate the linear discriminant functions.
    In this lecture, we estimate the linear discriminant functions.
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    6 λεπτά
    2 Μαΐ 2018
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  • 13. Classifying Data Points Using Linear Discriminant Functions

    13. Classifying Data Points Using Linear Discriminant Functions

    Students will learn how to classify data points using linear discriminant functions.
    Students will learn how to classify data points using linear discriminant functions.
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    3 λεπτά
    2 Μαΐ 2018
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  • 14. LDA Example 1

    14. LDA Example 1

    Students will see an example of applying linear discriminant analysis.
    Students will see an example of applying linear discriminant analysis.
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    14 λεπτά
    2 Μαΐ 2018
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  • 15. LDA Example 2

    15. LDA Example 2

    Another example of applying linear discriminant analysis is provided.
    Another example of applying linear discriminant analysis is provided.
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    18 λεπτά
    2 Μαΐ 2018
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  • 16. Summary: Linear Discriminant Analysis

    16. Summary: Linear Discriminant Analysis

    A summary of linear discriminant analysis is provided.
    A summary of linear discriminant analysis is provided.
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    2 λεπτά
    2 Μαΐ 2018
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  • 17. Section 3: Logistic Regression (First Lecture: Logistic Regression)

    17. Section 3: Logistic Regression (First Lecture: Logistic Regression)

    The method of logistic regression is introduced. Practice problems available at onlinemathtraining.
    The method of logistic regression is introduced. Practice problems available at onlinemathtraining.
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    1 λεπτά
    2 Μαΐ 2018
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  • 18. Logistic Regression Model of the Posterior Probability Function

    18. Logistic Regression Model of the Posterior Probability Function

    In this lecture, we model the posterior probability function.
    In this lecture, we model the posterior probability function.
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    3 λεπτά
    2 Μαΐ 2018
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  • 19. Estimating the Posterior Probability Function

    19. Estimating the Posterior Probability Function

    In this lecture, we introduce a strategy for estimating the posterior probability function.
    In this lecture, we introduce a strategy for estimating the posterior probability function.
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    9 λεπτά
    2 Μαΐ 2018
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  • 20. The Multivariate Newton-Raphson Method

    20. The Multivariate Newton-Raphson Method

    Students will learn how the Multivariate Newton-Raphson method is used to maximize a function.
    Students will learn how the Multivariate Newton-Raphson method is used to maximize a function.
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    9 λεπτά
    2 Μαΐ 2018
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  • 21. Maximizing the Log-Likelihood Function

    21. Maximizing the Log-Likelihood Function

    In this lecture, we apply the multivariate Newton-Raphson method to the log-likelihood function and learn about iterative reweighted least squares.
    In this lecture, we apply the multivariate Newton-Raphson method to the log-likelihood function and learn about iterative reweighted least squares.
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    14 λεπτά
    2 Μαΐ 2018
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  • 22. Example: Logistic Regression

    22. Example: Logistic Regression

    Students will learn how to apply logistic regression to solve a classification problem.
    Students will learn how to apply logistic regression to solve a classification problem.
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    10 λεπτά
    2 Μαΐ 2018
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  • 23. Summary: Logistic Regression

    23. Summary: Logistic Regression

    A summary of logistic regression is provided.
    A summary of logistic regression is provided.
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    1 λεπτά
    2 Μαΐ 2018
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  • 24. Section 4: Artificial Neural Networks (First Lecture: Artificial Neural Networks)

    24. Section 4: Artificial Neural Networks (First Lecture: Artificial Neural Networks)

    An introduction to artificial neural networks is provided. Practice problems available at onlinemathtraining.
    An introduction to artificial neural networks is provided. Practice problems available at onlinemathtraining.
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    36 δευτ.
    2 Μαΐ 2018
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    • Math for Machine Learning
    Ειδικού ενδιαφέροντος
    20181 σεζόν
    Learn the core topics of Machine Learning to open doors to data science and artificial intelligence. If you're looking to gain a solid foundation in Machine Learning, allowing you to study on your own schedule at a fraction of the cost it would take at a traditional university, to further your career goals, this online course is for you. Practice problems available at onlinemathtraining.
    Δημιουργοί και ηθοποιοί
    Σκηνοθέτες
    Richard Han
    Μετάδοση
    Richard Han
    Στούντιο
    Richard Han
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    English [CC]
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