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\nPredictive Analytics with TensorFlow 2.1: Using Statistics in Predictive Modeling\n

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\nIn this video, we will discuss some widely used statistical concepts required in predictive analytics, followed by some basic understanding of predictive modeling, such as random sampling, central limit theorem, hypothesis testing using...\nIn this video, we will discuss some widely used statistical concepts required in predictive analytics, followed by some basic understanding of predictive modeling, such as random sampling, central limit theorem, hypothesis testing using chi-square tests, correlation, expectation, variance and covariance, and so on. We will see an example of each of them.
• Look at the statistical model and central limit theorem
• Understand interquartile, range and quartile
• Look at hypothesis testing\n
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Resource Details

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Curator Rating
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Educator Rating
Not yet Rated
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Media Length
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13:20
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Grade
Higher Ed
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Subjects
Math
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Media Type
Instructional Videos
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Source:
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\nPackt - Data\n\n
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Date
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2019
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Language
English
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Audiences
For Teacher Use
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Usage Permissions
Fine Print: Educational Use
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Concepts

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standard deviation, data, variables, height, probability, coding, computer science, stem, blockchain
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Additional Tags

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predictive modeling, num py, machine learning, aws, angular, entire population, covariance lies, hypothesis test, average height, hypothesis, nonparametric models, quad trials, alternative hypothesis, average, software, null hypothesis, negative infinity, scipy, data points, numerical data, positive infinity, sample, predictive analytics, react, c++, covariance, programming, statistical model, c#, python, equal, data set, simple
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Classroom Considerations

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Best For: Explaining a topic
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