Name: Crash Course Statistics - Season 1 Episode 36 Supervised Machine Learning
Released: 01 Jan 1970
Rating: 2.00
Cast: Adriene Hill

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Crash Course Statistics - Season 1 Episode 36 Supervised Machine Learning

Trailer

We've talked a lot about modeling data and making inferences about it, but today we're going to look towards the future at how machine learning is being used to build models to predict future outcomes. We'll discuss three popular types of supervised machine learning models: Logistic Regression, Linear discriminant Analysis (or LDA) and K Nearest Neighbors (or KNN). For a broader overview of machine learning, check out our episode in Crash Course Computer Science!

Year: 2019

Genre:

Country: United States of America

Studio: YouTube

Director:

Cast: Adriene Hill

Crew:

First Air Date: Jan 24, 2018

Last Air date: Jan 09, 2019

Season: 1 Season

Episode: 44 Episode

Runtime: 13 minutes

IMDb: 2.00/10 by 1.00 users

Popularity: 2.971

Language: English

Keyword : mathematics, educational, statistics, statistician

Season Season 1

Episode What Is Statistics Mathematical Thinking Mean, Median, and Mode: Measures of Central Tendency Measures of Spread Charts Are Like Pasta - Data Visualization Part 1 Plots, Outliers, and Justin Timberlake: Data Visualization Part 2 The Shape of Data: Distributions Correlation Doesn’t Equal Causation Controlled Experiments Sampling Methods and Bias with Surveys Science Journalism Henrietta Lacks, the Tuskegee Experiment, and Ethical Data Collection Probability Part 1: Rules and Patterns Probability Part 2: Updating Your Beliefs with Bayes The Binomial Distribution Geometric Distributions and The Birthday Paradox Randomness Z-Scores and Percentiles The Normal Distribution Confidence Intervals How P-Values Help Us Test Hypotheses P-Value Problems Playing with Power: P-Values Pt 3 You Know I’m All About that Bayes Bayes in Science and Everyday Life Test Statistics T-Tests: A Matched Pair Made in Heaven Degrees of Freedom and Effect Sizes Chi-Square Tests P-Hacking The Replication Crisis Regression ANOVA ANOVA Part 2: Dealing with Intersectional Groups Fitting Models Is like Tetris Supervised Machine Learning Unsupervised Machine Learning Intro to Big Data Big Data Problems Statistics in the Courts Neural Networks War When Predictions Fail When Predictions Succeed