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种子名称： [Udemy] Statistics & Mathematics for Data Science in Python [2020, ENG]
文件类型： 视频
文件数目： 72个文件
文件大小： 720.75 MB
收录时间： 2022-1-2 12:35
已经下载： 3次
资源热度： 214
最近下载： 2024-12-22 19:53

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[Udemy] Statistics & Mathematics for Data Science in Python [2020, ENG].torrent

5. Confidence Intervals & Hypothesis Testing/10. Summary.mp4503.67KB

1. Google Colab for Data Science/8. Summary.mp4563.49KB

8. Natural Language Processing/9. Summary.mp4649.49KB

3. Distribution Types/1. Introduction.mp4685.56KB

2. Vocabulary & Descriptive Statistics/1. Introduction.mp4688.01KB

6. Regression & Predictions/1. Introduction.mp4721.31KB

7. Classification Modeling/11. Summary.mp4760.11KB

8. Natural Language Processing/1. Introduction.mp4770.6KB

4. Inferential Statistics with Visualizations/7. Summary.mp4831.27KB

5. Confidence Intervals & Hypothesis Testing/1. Introduction.mp4852.66KB

7. Classification Modeling/1. Introduction.mp4899.62KB

2. Vocabulary & Descriptive Statistics/7. Summary.mp4923.97KB

1. Google Colab for Data Science/2. Introduction.mp4974.6KB

4. Inferential Statistics with Visualizations/1. Introduction.mp41.02MB

6. Regression & Predictions/12. Summary.mp41.09MB

1. Google Colab for Data Science/3. Google Drive & Colab Introduction.mp42.18MB

3. Distribution Types/8. Summary.mp42.5MB

1. Google Colab for Data Science/1. Course Overview.mp42.63MB

1. Google Colab for Data Science/7. Sharing a Colab Notebook.mp42.9MB

3. Distribution Types/2. Introduction to Probability Distributions.mp43.11MB

1. Google Colab for Data Science/4. Documentation Exploration.mp44.59MB

7. Classification Modeling/8. Random Forest.mp45.02MB

8. Natural Language Processing/6. Finding Features of Textual Data.mp45.23MB

5. Confidence Intervals & Hypothesis Testing/3. Introduction to Confidence Intervals & Tests.mp46.11MB

7. Classification Modeling/6. K-Nearest Neighbors.mp46.41MB

8. Natural Language Processing/7. Naive Bayes with NLTK.mp46.64MB

8. Natural Language Processing/4. For Loop Creation of 8.2.mp46.95MB

8. Natural Language Processing/3. NLTK to Examine Text.mp47.6MB

7. Classification Modeling/5. Logistic Regression.mp47.99MB

8. Natural Language Processing/5. Movie Reviews Text Analysis & Frequency.mp48.22MB

3. Distribution Types/5. Poisson Distribution.mp48.58MB

2. Vocabulary & Descriptive Statistics/2. Introduction to General Statistical Vocabulary.mp49.4MB

6. Regression & Predictions/6. Ridge Regression.mp49.67MB

6. Regression & Predictions/9. Random Forest Regression.mp49.8MB

7. Classification Modeling/10. Model Hyper Tuning & Optimization.mp410.16MB

7. Classification Modeling/7. SVM.mp410.27MB

7. Classification Modeling/2. Preparation Part 1 Loading & Exploring Penguins Data.mp410.4MB

8. Natural Language Processing/2. Data Loading & Exploration.mp410.49MB

3. Distribution Types/3. Uniform Distribution.mp411.02MB

6. Regression & Predictions/5. Polynomial Regression.mp411.17MB

2. Vocabulary & Descriptive Statistics/6. Correlation Coefficient.mp411.39MB

4. Inferential Statistics with Visualizations/5. Scatter Plots.mp411.44MB

5. Confidence Intervals & Hypothesis Testing/2. Seaborn Sample Data & Fitting.mp411.5MB

3. Distribution Types/4. Binomial Distribution.mp411.57MB

7. Classification Modeling/4. Naive Bayes.mp411.73MB

6. Regression & Predictions/8. ElasticNet Regression.mp412.14MB

1. Google Colab for Data Science/5. Importing Data from Google Drive to Pandas DataFrame.mp412.33MB

4. Inferential Statistics with Visualizations/4. Box Plots.mp412.72MB

6. Regression & Predictions/7. Lasso Regression.mp412.76MB

4. Inferential Statistics with Visualizations/3. Histograms.mp412.77MB

1. Google Colab for Data Science/6. Importing Data from OneDrive to Pandas DataFrame.mp412.85MB

5. Confidence Intervals & Hypothesis Testing/4. Assuming Normality.mp413.35MB

4. Inferential Statistics with Visualizations/2. Bar Charts.mp414.36MB

5. Confidence Intervals & Hypothesis Testing/8. ANOVA.mp414.39MB

3. Distribution Types/6. Normal Distribution.mp415.11MB

7. Classification Modeling/3. Preparation Part 2 Cleaning & Preparing Penguins Data.mp415.94MB

4. Inferential Statistics with Visualizations/6. Advanced Visualizations.mp415.95MB

2. Vocabulary & Descriptive Statistics/5. Measures of Center, Essential Analytics.mp416.14MB

5. Confidence Intervals & Hypothesis Testing/5. Normal DataProbability Plots with Means.mp416.65MB

2. Vocabulary & Descriptive Statistics/4. Summarizing Data with Counts.mp416.91MB

3. Distribution Types/7. Fitting Distributions - Advanced.mp417.05MB

6. Regression & Predictions/11. Model Hyper Tuning & Optimization.mp417.43MB

6. Regression & Predictions/2. Preparation Part 1 Loading & Exploring Diamonds Data.mp418.39MB

2. Vocabulary & Descriptive Statistics/3. Variable Types within Data.mp419.13MB

8. Natural Language Processing/8. Cosine Similarity Between Texts.mp419.84MB

6. Regression & Predictions/4. Linear Regression.mp420.72MB

7. Classification Modeling/9. Model Comparison Tool.mp420.88MB

6. Regression & Predictions/10. Model Comparison Tool.mp421.89MB

5. Confidence Intervals & Hypothesis Testing/9. Non-Normal Data & Bootstrap.mp423.4MB

5. Confidence Intervals & Hypothesis Testing/6. Normal Data Categorical Confidence Intervals.mp425.48MB

6. Regression & Predictions/3. Preparation Part 2 Categorical Coding & Data Splitting.mp425.79MB

5. Confidence Intervals & Hypothesis Testing/7. Normal Data Quantitative Confidence Intervals.mp428MB