Hypothesis Testing and Classification

Everyone
  • 17 videos | 1h 50m 32s
  • Includes Assessment
This course will cover the basics of anomaly detection and classification: for these tasks there are methods coming from either statistics or machine learning that are built on different principles. As well as the fundamentals of hypothesis testing, which is the formalization of scientific inquiry. This delicate statistical setup obeys a certain set of rules that will be explained and put in context with classification.

WHAT YOU WILL LEARN

  • Understand what classification is
    Know what binary classification is
    Learn more about binary classification
    Know how to evaluate a classifier and understand the metrics used to do so
    Know what hypothesis testing is
    Understand what a confidence interval is
    Understand hypothesis testing when the distribution is binomial
    Know how to use the statistics obtained in an appropriate manner
  • Be able to apply the p-value to your calculation
    Know how to estimate likelihood
    Know how to use non-statistical classifiers
    Understand the perceptron algorithm
    Understand the proof behind the perceptron algorithm
    Be able to use svms for more complicated problems
    Be able to use the methods for estimating the parameters of logistic regression
    Know how statistical techniques could be misapplied

IN THIS COURSE

  • 1m 5s
    Meet the instructors and learn what classification is. FREE ACCESS
  • 1m 51s
    Learn about a common classification problem.  FREE ACCESS
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    3.  What Are Anomalies? What Is Fraud? Spams? Part 2
    3m 28s
    Gain more understanding of binary classification.  FREE ACCESS
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    4.  What Are Anomalies? What is Fraud? Spams? Part 3
    5m 53s
    Learn about errors in classification analysis. FREE ACCESS
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    5.  False Positive/Negative, Precision/Recall, F-Score
    7m 13s
    Learn how to evaluate a classifier using the metrics presented.  FREE ACCESS
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    6.  Hypothesis Testing
    1m 20s
    Learn what a hypothesis test is.  FREE ACCESS
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    7.  Confidence Intervals
    6m 46s
    Learn about confidence intervals and how they relate to hypothesis testing. FREE ACCESS
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    8.  Validity Of Binomial Distribution
    5m 45s
    Learn about how hypothesis testing works with a binomial distribution.  FREE ACCESS
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    9.  Misuses Of Statistics
    9m 6s
    Learn how not to misuse your statistical output. FREE ACCESS
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    10.  P-Value
    9m 39s
    Learn about the p-value and how it works. FREE ACCESS
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    11.  Methods Of Estimating Likelihood
    6m 42s
    Learn about estimating likelihood.  FREE ACCESS
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    12.  Support Vector Machine: Non-Statistical Classifier
    8m 33s
    Find out how non-statistical classifiers work.  FREE ACCESS
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    13.  Perceptron
    10m 27s
    Learn about a simple classifier with an elegant interpretation. FREE ACCESS
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    14.  Perceptron Proof
    8m 10s
    Learn about the proof behind our claim in the previous video. FREE ACCESS
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    15.  Perceptron & Data That Is Not Linearly Separable
    10m 16s
    Apply some simple modifications to allow SVMs to be used in more complicated settings.  FREE ACCESS
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    16.  Estimating The Parameters Of Logistic Regression
    7m 49s
    Find out how you can estimate the parameters of logistical regression. FREE ACCESS
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    17.  Misapplications Of Statistical Techniques
    6m 27s
    Learn what not to do with these statistical methods.  FREE ACCESS

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