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【影视】 [FreeCoursesOnline.Me] Pluralsight - Interpreting Data Using Statistical Models with Python

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05.Implementing Predictive Models for Categorical Data/05.06.Demo Selecting..Information.mp4 55.7 MB
03.Performing Hypothesis Testing in Python/03.07.Demo Two-way ANOVA.mp4 21.6 MB
03.Performing Hypothesis Testing in Python/03.02.Demo Preparing Data for Hypothesis Testing.mp4 19.8 MB
03.Performing Hypothesis Testing in Python/03.08.Demo Chi2 Analysis.mp4 18.4 MB
03.Performing Hypothesis Testing in Python/03.04.Demo Performing Welch's t-test.mp4 16.2 MB
03.Performing Hypothesis Testing in Python/03.03.Demo Performing the Independent t-test.mp4 15.8 MB
05.Implementing Predictive Models for Categorical Data/05.05.Demo Performing Classification Using Logistic Regression.mp4 15.6 MB
04.Implementing Predictive Models for Continuous Data/04.05.Demo Preparing Data for Simple Linear Regression.mp4 14.9 MB
04.Implementing Predictive Models for Continuous Data/04.08.Demo Selecting..Using Correlations.mp4 13.8 MB
03.Performing Hypothesis Testing in Python/03.06.Demo One-way ANOVA and Tukey's Honest Significant Difference Test.mp4 13.2 MB
03.Performing Hypothesis Testing in Python/03.05.Demo Performing the Paired Difference t-test.mp4 12.8 MB
04.Implementing Predictive Models for Continuous Data/04.06.Demo Linear ..Techniques.mp4 12.5 MB
02.Understanding Inferential Statistics/02.10.One-way ANOVA.mp4 12.4 MB
02.Understanding Inferential Statistics/02.09.Other Types of t-tests.mp4 12.2 MB
01.Course Overview/01.01.Course Overview.mp4 11.7 MB
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【影视】 Pluralsight Path. Building Statistical and Mathematical Models with R (2020)

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B4. Applying Linear Algebra with R (Brandon Strain, 2020)/8. Implementing Matrix Decomposition/2. Demo - Implementing Matrix Decomposition.mp4 32.3 MB
B4. Applying Linear Algebra with R (Brandon Strain, 2020)/4. Getting Weird - Inverting, Transposing, and Row Equivalence/1. Getting Weird.mp4 24.5 MB
C3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/5. Predictions on Commodities Data.mp4 24.0 MB
C3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/4. Point Estimates and Confidence Intervals.mp4 22.1 MB
B4. Applying Linear Algebra with R (Brandon Strain, 2020)/7. Calculating the kth Item in a Series/3. Demo - Calculating the kth Item in a Series.mp4 21.0 MB
B3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/2. Demo - Manifold Learning Using Metric and Non-metric MDS.mp4 21.0 MB
B1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/4. Demo - Linear Discriminant Analysis (LDA) and Visualization.mp4 20.4 MB
B1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/8. Demo - Robust Regression Using the Boston Housing Dataset.mp4 20.4 MB
B4. Applying Linear Algebra with R (Brandon Strain, 2020)/2. Working with Vectors and Matrices in R/1. Working with Vectors and Matrices in R.mp4 20.3 MB
C2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/2. Demo - Performing Bootstrapping on Real Data.mp4 20.1 MB
A2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/04. Demo - 8 Queens - Calculating Number of Attacks.mp4 20.0 MB
C2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/1. Demo - Bootstrap Statistics and Sample Statistics.mp4 19.8 MB
C3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/3. Simulating Random Walk with MC.mp4 19.6 MB
A2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/9. Demo - Eulers Method and Numerical Instability.mp4 19.5 MB
B3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/3. Demo - Manifold Learning Using t-SNE, Isomap, and LLE.mp4 17.5 MB
B3. Performing Dimension Analysis with R (Janani Ravi, 2020)/4. Performing Dimensional Analysis for Categorical Data/3. Demo - Performing Linear Discriminant Analysis on Glass Data.mp4 17.4 MB
B1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/08. Demo - Quantitative and Qualitative Analysis of Bi.mp4 17.3 MB
B1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/09. Demo - Visualizing and Interpreting State Occupancy Probabilities.mp4 17.3 MB
B4. Applying Linear Algebra with R (Brandon Strain, 2020)/5. Solving Linear Equations/1. Solving Linear Equations.mp4 17.2 MB
A1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/7. Demo - Setting up Helper Functions to Solve the 8 Queens Optimization Prob.mp4 17.0 MB

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