[TutorialPace.com] Lynda - Python Statistics Essential Training - [TP]
| 文件类型 | 收录时间 | 最后活跃 | 资源热度 | 文件大小 | 文件数量 |
|---|---|---|---|---|---|
| 视频 | 2019-5-18 12:25 | 2024-12-27 16:19 | 112 | 430.99 MB | 39 |
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文件列表
- 4.4. Introduction to Statistical Inference/29.✓ Challenge - Bootstrapping grades.mp41.12MB
- 0.Introduction/02.What you need to know.mp41.23MB
- 3.3. Visualizing and Describing Data/22.✓ Challenge - More email analytics.mp41.33MB
- 5.5. Introduction to Statistical Modeling/31.Statistical modeling.mp42.39MB
- 5.5. Introduction to Statistical Modeling/37.✓ Challenge - Explaining baby weight at birth.mp42.8MB
- 4.4. Introduction to Statistical Inference/24.Statistical inference.mp42.88MB
- 6.Conclusion/39.Next steps.mp42.9MB
- 0.Introduction/03.Using the exercise files.mp43MB
- 2.2. Importing and Cleaning Data/08.The structure of data.mp43.05MB
- 2.2. Importing and Cleaning Data/12.✓ Challenge - Personal email analytics.mp43.39MB
- 5.5. Introduction to Statistical Modeling/38.✓ Solution - Explaining baby weight at birth.mp44.02MB
- 4.4. Introduction to Statistical Inference/30.✓ Solution - Bootstrapping grades.mp44.29MB
- 3.3. Visualizing and Describing Data/23.✓ Solution - More email analytics.mp44.63MB
- 1.1. Installation and Setup/06.Working with Jupyter Notebook.mp46.53MB
- 0.Introduction/01.Welcome.mp46.91MB
- 1.1. Installation and Setup/04.Install Anaconda Python on OS X.mp48.1MB
- 1.1. Installation and Setup/07.Using Python in the cloud.mp48.8MB
- 3.3. Visualizing and Describing Data/15.Describe distributions.mp49.07MB
- 2.2. Importing and Cleaning Data/13.✓ Solution - Personal email analytics.mp410MB
- 1.1. Installation and Setup/05.Install Anaconda Python on Windows.mp410.32MB
- 5.5. Introduction to Statistical Modeling/35.Logistic regression.mp411.09MB
- 2.2. Importing and Cleaning Data/09.Create tidy data tables.mp411.16MB
- 3.3. Visualizing and Describing Data/20.Plot categorical variables.mp411.94MB
- 3.3. Visualizing and Describing Data/19.Describe categorical variables.mp411.97MB
- 5.5. Introduction to Statistical Modeling/34.Cross validation.mp413.1MB
- 4.4. Introduction to Statistical Inference/28.p values and confidence intervals.mp413.35MB
- 5.5. Introduction to Statistical Modeling/33.Goodness of fit.mp413.99MB
- 5.5. Introduction to Statistical Modeling/32.Fitting models to data.mp416.49MB
- 3.3. Visualizing and Describing Data/17.Plots of two quantitative variables.mp416.72MB
- 4.4. Introduction to Statistical Inference/26.Bootstrapping.mp417.06MB
- 4.4. Introduction to Statistical Inference/25.Confidence intervals.mp417.18MB
- 3.3. Visualizing and Describing Data/16.Plot distributions.mp418.79MB
- 2.2. Importing and Cleaning Data/10.Introducing pandas.mp418.89MB
- 5.5. Introduction to Statistical Modeling/36.Bayesian inference.mp419.04MB
- 4.4. Introduction to Statistical Inference/27.Hypothesis testing.mp419.52MB
- 3.3. Visualizing and Describing Data/14.The power of visualization.mp420.03MB
- 3.3. Visualizing and Describing Data/18.More quantitative variables.mp421.5MB
- 3.3. Visualizing and Describing Data/21.Personal email analytics.mp428.99MB
- 2.2. Importing and Cleaning Data/11.Data cleaning.mp433.44MB
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