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

File Name

Size

7. Classification Modeling/12. Quiz 7.html

160 B

6. Regression & Predictions/13. Quiz 6.html

160 B

1. Google Colab for Data Science/9. Quiz 1.html

160 B

4. Inferential Statistics with Visualizations/8. Quiz 4.html

160 B

2. Vocabulary & Descriptive Statistics/8. Quiz-2.html

160 B

5. Confidence Intervals & Hypothesis Testing/11. Quiz 5.html

160 B

3. Distribution Types/9. Quiz 3.html

160 B

8. Natural Language Processing/10. Quiz 8.html

160 B

8. Natural Language Processing/11. Project Resource File.html

528 B

5. Confidence Intervals & Hypothesis Testing/10. Summary.srt

1.1 kB

1. Google Colab for Data Science/8. Summary.srt

1.1 kB

8. Natural Language Processing/9. Summary.srt

1.2 kB

3. Distribution Types/1. Introduction.srt

1.2 kB

8. Natural Language Processing/1. Introduction.srt

1.2 kB

6. Regression & Predictions/1. Introduction.srt

1.3 kB

7. Classification Modeling/11. Summary.srt

1.3 kB

2. Vocabulary & Descriptive Statistics/1. Introduction.srt

1.4 kB

7. Classification Modeling/1. Introduction.srt

1.5 kB

4. Inferential Statistics with Visualizations/7. Summary.srt

1.6 kB

5. Confidence Intervals & Hypothesis Testing/1. Introduction.srt

1.6 kB

2. Vocabulary & Descriptive Statistics/7. Summary.srt

1.9 kB

4. Inferential Statistics with Visualizations/1. Introduction.srt

2.0 kB

6. Regression & Predictions/12. Summary.srt

2.1 kB

1. Google Colab for Data Science/2. Introduction.srt

2.2 kB

3. Distribution Types/8. Summary.srt

5.2 kB

1. Google Colab for Data Science/3. Google Drive & Colab Introduction.srt

5.2 kB

1. Google Colab for Data Science/1. Course Overview.srt

6.0 kB

1. Google Colab for Data Science/1.1 Google Colab for Data Science.zip

6.2 kB

3. Distribution Types/2. Introduction to Probability Distributions.srt

6.2 kB

1. Google Colab for Data Science/7. Sharing a Colab Notebook.srt

6.5 kB

8. Natural Language Processing/6. Finding Features of Textual Data.srt

7.5 kB

1. Google Colab for Data Science/4. Documentation Exploration.srt

7.9 kB

7. Classification Modeling/8. Random Forest.srt

8.0 kB

7. Classification Modeling/6. K-Nearest Neighbors.srt

9.2 kB

8. Natural Language Processing/7. Naive Bayes with NLTK.srt

11 kB

8. Natural Language Processing/4. For Loop Creation of 8.2.srt

12 kB

5. Confidence Intervals & Hypothesis Testing/3. Introduction to Confidence Intervals & Tests.srt

13 kB

8. Natural Language Processing/3. NLTK to Examine Text.srt

14 kB

6. Regression & Predictions/6. Ridge Regression.srt

14 kB

8. Natural Language Processing/5. Movie Reviews Text Analysis & Frequency.srt

14 kB

8. Natural Language Processing/2. Data Loading & Exploration.srt

14 kB

7. Classification Modeling/7. SVM.srt

14 kB

7. Classification Modeling/5. Logistic Regression.srt

14 kB

6. Regression & Predictions/9. Random Forest Regression.srt

14 kB

6. Regression & Predictions/5. Polynomial Regression.srt

16 kB

3. Distribution Types/5. Poisson Distribution.srt

16 kB

7. Classification Modeling/10. Model Hyper Tuning & Optimization.srt

16 kB

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

16 kB

6. Regression & Predictions/7. Lasso Regression.srt

16 kB

6. Regression & Predictions/8. ElasticNet Regression.srt

17 kB

2. Vocabulary & Descriptive Statistics/4. Summarizing Data with Counts.srt

18 kB

2. Vocabulary & Descriptive Statistics/1.1 Vocabulary & Descriptive Statistics.zip

19 kB

7. Classification Modeling/2. Preparation Part 1 Loading & Exploring Penguins Data.srt

19 kB

4. Inferential Statistics with Visualizations/5. Scatter Plots.srt

19 kB

2. Vocabulary & Descriptive Statistics/6. Correlation Coefficient.srt

19 kB

3. Distribution Types/7. Fitting Distributions - Advanced.srt

19 kB

3. Distribution Types/3. Uniform Distribution.srt

20 kB

6. Regression & Predictions/11. Model Hyper Tuning & Optimization.srt

21 kB

2. Vocabulary & Descriptive Statistics/2. Introduction to General Statistical Vocabulary.srt

21 kB

7. Classification Modeling/4. Naive Bayes.srt

22 kB

4. Inferential Statistics with Visualizations/3. Histograms.srt

22 kB

1. Google Colab for Data Science/6. Importing Data from OneDrive to Pandas DataFrame.srt

22 kB

3. Distribution Types/4. Binomial Distribution.srt

22 kB

5. Confidence Intervals & Hypothesis Testing/4. Assuming Normality.srt

22 kB

4. Inferential Statistics with Visualizations/4. Box Plots.srt

22 kB

5. Confidence Intervals & Hypothesis Testing/8. ANOVA.srt

22 kB

3. Distribution Types/6. Normal Distribution.srt

23 kB

1. Google Colab for Data Science/5. Importing Data from Google Drive to Pandas DataFrame.srt

24 kB

4. Inferential Statistics with Visualizations/6. Advanced Visualizations.srt

24 kB

4. Inferential Statistics with Visualizations/2. Bar Charts.srt

24 kB

2. Vocabulary & Descriptive Statistics/3. Variable Types within Data.srt

25 kB

2. Vocabulary & Descriptive Statistics/5. Measures of Center, Essential Analytics.srt

26 kB

6. Regression & Predictions/4. Linear Regression.srt

27 kB

5. Confidence Intervals & Hypothesis Testing/5. Normal DataProbability Plots with Means.srt

27 kB

7. Classification Modeling/3. Preparation Part 2 Cleaning & Preparing Penguins Data.srt

30 kB

6. Regression & Predictions/2. Preparation Part 1 Loading & Exploring Diamonds Data.srt

32 kB

6. Regression & Predictions/10. Model Comparison Tool.srt

33 kB

8. Natural Language Processing/8. Cosine Similarity Between Texts.srt

34 kB

7. Classification Modeling/9. Model Comparison Tool.srt

36 kB

5. Confidence Intervals & Hypothesis Testing/9. Non-Normal Data & Bootstrap.srt

37 kB

6. Regression & Predictions/3. Preparation Part 2 Categorical Coding & Data Splitting.srt

39 kB

5. Confidence Intervals & Hypothesis Testing/6. Normal Data Categorical Confidence Intervals.srt

43 kB

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

44 kB

8. Natural Language Processing/11.1 16155477.zip

188 kB

8. Natural Language Processing/1.1 Natural Language Processing.zip

254 kB

3. Distribution Types/1.1 Distribution Types.zip

254 kB

6. Regression & Predictions/1.1 Regression & Predictions.zip

398 kB

5. Confidence Intervals & Hypothesis Testing/1.1 Confidence Intervals & Hypothesis Testing.zip

412 kB

7. Classification Modeling/1.1 Classification Modeling.zip

424 kB

5. Confidence Intervals & Hypothesis Testing/10. Summary.mp4

504 kB

1. Google Colab for Data Science/8. Summary.mp4

564 kB

8. Natural Language Processing/9. Summary.mp4

650 kB

3. Distribution Types/1. Introduction.mp4

686 kB

2. Vocabulary & Descriptive Statistics/1. Introduction.mp4

688 kB

6. Regression & Predictions/1. Introduction.mp4

721 kB

7. Classification Modeling/11. Summary.mp4

760 kB

8. Natural Language Processing/1. Introduction.mp4

771 kB

4. Inferential Statistics with Visualizations/7. Summary.mp4

831 kB

5. Confidence Intervals & Hypothesis Testing/1. Introduction.mp4

853 kB

4. Inferential Statistics with Visualizations/1.1 Inferential Statistics with Visualizations.zip

860 kB

7. Classification Modeling/1. Introduction.mp4

900 kB

2. Vocabulary & Descriptive Statistics/7. Summary.mp4

924 kB

1. Google Colab for Data Science/2. Introduction.mp4

975 kB

4. Inferential Statistics with Visualizations/1. Introduction.mp4

1.0 MB

6. Regression & Predictions/12. Summary.mp4

1.1 MB

1. Google Colab for Data Science/3. Google Drive & Colab Introduction.mp4

2.2 MB

3. Distribution Types/8. Summary.mp4

2.5 MB

1. Google Colab for Data Science/1. Course Overview.mp4

2.6 MB

1. Google Colab for Data Science/7. Sharing a Colab Notebook.mp4

2.9 MB

3. Distribution Types/2. Introduction to Probability Distributions.mp4

3.1 MB

1. Google Colab for Data Science/4. Documentation Exploration.mp4

4.6 MB

7. Classification Modeling/8. Random Forest.mp4

5.0 MB

8. Natural Language Processing/6. Finding Features of Textual Data.mp4

5.2 MB

5. Confidence Intervals & Hypothesis Testing/3. Introduction to Confidence Intervals & Tests.mp4

6.1 MB

7. Classification Modeling/6. K-Nearest Neighbors.mp4

6.4 MB

8. Natural Language Processing/7. Naive Bayes with NLTK.mp4

6.6 MB

8. Natural Language Processing/4. For Loop Creation of 8.2.mp4

7.0 MB

8. Natural Language Processing/3. NLTK to Examine Text.mp4

7.6 MB

7. Classification Modeling/5. Logistic Regression.mp4

8.0 MB

8. Natural Language Processing/5. Movie Reviews Text Analysis & Frequency.mp4

8.2 MB

3. Distribution Types/5. Poisson Distribution.mp4

8.6 MB

2. Vocabulary & Descriptive Statistics/2. Introduction to General Statistical Vocabulary.mp4

9.4 MB

6. Regression & Predictions/6. Ridge Regression.mp4

9.7 MB

6. Regression & Predictions/9. Random Forest Regression.mp4

9.8 MB

7. Classification Modeling/10. Model Hyper Tuning & Optimization.mp4

10 MB

7. Classification Modeling/7. SVM.mp4

10 MB

7. Classification Modeling/2. Preparation Part 1 Loading & Exploring Penguins Data.mp4

10 MB

8. Natural Language Processing/2. Data Loading & Exploration.mp4

10 MB

3. Distribution Types/3. Uniform Distribution.mp4

11 MB

6. Regression & Predictions/5. Polynomial Regression.mp4

11 MB

2. Vocabulary & Descriptive Statistics/6. Correlation Coefficient.mp4

11 MB

4. Inferential Statistics with Visualizations/5. Scatter Plots.mp4

11 MB

5. Confidence Intervals & Hypothesis Testing/2. Seaborn Sample Data & Fitting.mp4

12 MB

3. Distribution Types/4. Binomial Distribution.mp4

12 MB

7. Classification Modeling/4. Naive Bayes.mp4

12 MB

6. Regression & Predictions/8. ElasticNet Regression.mp4

12 MB

1. Google Colab for Data Science/5. Importing Data from Google Drive to Pandas DataFrame.mp4

12 MB

4. Inferential Statistics with Visualizations/4. Box Plots.mp4

13 MB

6. Regression & Predictions/7. Lasso Regression.mp4

13 MB

4. Inferential Statistics with Visualizations/3. Histograms.mp4

13 MB

1. Google Colab for Data Science/6. Importing Data from OneDrive to Pandas DataFrame.mp4

13 MB

5. Confidence Intervals & Hypothesis Testing/4. Assuming Normality.mp4

13 MB

4. Inferential Statistics with Visualizations/2. Bar Charts.mp4

14 MB

5. Confidence Intervals & Hypothesis Testing/8. ANOVA.mp4

14 MB

3. Distribution Types/6. Normal Distribution.mp4

15 MB

7. Classification Modeling/3. Preparation Part 2 Cleaning & Preparing Penguins Data.mp4

16 MB

4. Inferential Statistics with Visualizations/6. Advanced Visualizations.mp4

16 MB

2. Vocabulary & Descriptive Statistics/5. Measures of Center, Essential Analytics.mp4

16 MB

5. Confidence Intervals & Hypothesis Testing/5. Normal DataProbability Plots with Means.mp4

17 MB

2. Vocabulary & Descriptive Statistics/4. Summarizing Data with Counts.mp4

17 MB

3. Distribution Types/7. Fitting Distributions - Advanced.mp4

17 MB

6. Regression & Predictions/11. Model Hyper Tuning & Optimization.mp4

17 MB

6. Regression & Predictions/2. Preparation Part 1 Loading & Exploring Diamonds Data.mp4

18 MB

2. Vocabulary & Descriptive Statistics/3. Variable Types within Data.mp4

19 MB

8. Natural Language Processing/8. Cosine Similarity Between Texts.mp4

20 MB

6. Regression & Predictions/4. Linear Regression.mp4

21 MB

7. Classification Modeling/9. Model Comparison Tool.mp4

21 MB

6. Regression & Predictions/10. Model Comparison Tool.mp4

22 MB

5. Confidence Intervals & Hypothesis Testing/9. Non-Normal Data & Bootstrap.mp4

23 MB

5. Confidence Intervals & Hypothesis Testing/6. Normal Data Categorical Confidence Intervals.mp4

26 MB

6. Regression & Predictions/3. Preparation Part 2 Categorical Coding & Data Splitting.mp4

26 MB

5. Confidence Intervals & Hypothesis Testing/7. Normal Data Quantitative Confidence Intervals.mp4

28 MB