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[Tutorialsplanet.NET] Udemy - Learning Python for Data Analysis and Visualization

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[Tutorialsplanet.NET] Udemy - Learning Python for Data Analysis and Visualization

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种子哈希:645e7d6ca37f7cc8f77c256b5daf3542aed34082
文件大小: 3.67G
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收录时间:2022-02-07
最近下载:2025-07-23

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文件列表

  • 10. Machine Learning/16. Decision Trees and Random Forests.mp4 160.4 MB
  • 10. Machine Learning/9. Logistic Regression Part 4.mp4 102.7 MB
  • 9. Example Projects/12. Data Project - Stock Market Analysis Part 5.mp4 98.5 MB
  • 10. Machine Learning/19. Natural Language Processing Part 3.mp4 97.0 MB
  • 10. Machine Learning/13. Support Vector Machines - Part 2.mp4 90.0 MB
  • 9. Example Projects/17. Data Project - Election Analysis Part 4.mp4 86.1 MB
  • 11. Appendix Statistics Overview/9. Hypothesis Testing and Confidence Intervals.mp4 82.7 MB
  • 10. Machine Learning/5. Linear Regression Part 4.mp4 82.5 MB
  • 10. Machine Learning/11. Multi Class Classification Part 2 - k Nearest Neighbor.mp4 77.1 MB
  • 10. Machine Learning/6. Logistic Regression Part 1.mp4 75.3 MB
  • 10. Machine Learning/4. Linear Regression Part 3.mp4 72.2 MB
  • 10. Machine Learning/10. Multi Class Classification Part 1 - Logistic Regression.mp4 71.1 MB
  • 10. Machine Learning/20. Natural Language Processing Part 4.mp4 70.4 MB
  • 10. Machine Learning/15. Naive Bayes Part 2.mp4 68.7 MB
  • 10. Machine Learning/12. Support Vector Machines Part 1.mp4 68.1 MB
  • 8. Data Visualization/3. Kernel Density Estimate Plots.mp4 64.9 MB
  • 10. Machine Learning/18. Natural Language Processing Part 2.mp4 62.6 MB
  • 10. Machine Learning/2. Linear Regression Part 1.mp4 61.5 MB
  • 9. Example Projects/9. Data Project - Stock Market Analysis Part 2.mp4 59.6 MB
  • 9. Example Projects/15. Data Project - Election Analysis Part 2.mp4 59.1 MB
  • 4. Intro to Pandas/2. DataFrames.mp4 55.4 MB
  • 10. Machine Learning/3. Linear Regression Part 2.mp4 55.1 MB
  • 10. Machine Learning/7. Logistic Regression Part 2.mp4 54.3 MB
  • 10. Machine Learning/1. Introduction to Machine Learning with SciKit Learn.mp4 48.4 MB
  • 4. Intro to Pandas/9. Summary Statistics.mp4 48.3 MB
  • 9. Example Projects/14. Data Project - Election Analysis Part 1.mp4 46.7 MB
  • 10. Machine Learning/17. Natural Language Processing Part 1.mp4 46.0 MB
  • 13. Appendix Web Scraping with Python/2. Web Scraping Part 2.mp4 46.0 MB
  • 7. Working with Data Part 3/3. Aggregation.mp4 45.9 MB
  • 12. Appendix SQL and Python/1. Introduction to SQL with Python.mp4 45.9 MB
  • 9. Example Projects/3. Titanic Project - Part 1.mp4 45.4 MB
  • 11. Appendix Statistics Overview/4. Binomial Distribution.mp4 43.8 MB
  • 3. Learning Numpy/7. Array Processing.mp4 43.0 MB
  • 11. Appendix Statistics Overview/5. Poisson Distribution.mp4 42.2 MB
  • 9. Example Projects/10. Data Project - Stock Market Analysis Part 3.mp4 42.0 MB
  • 10. Machine Learning/8. Logistic Regression Part 3.mp4 41.6 MB
  • 2. Setup/3. iPythonJupyter Notebook Overview.mp4 41.4 MB
  • 9. Example Projects/16. Data Project - Election Analysis Part 3.mp4 41.0 MB
  • 8. Data Visualization/7. Heatmaps and Clustered Matrices.mp4 40.9 MB
  • 9. Example Projects/4. Titanic Project - Part 2.mp4 40.8 MB
  • 13. Appendix Web Scraping with Python/1. Web Scraping Part 1.mp4 39.1 MB
  • 11. Appendix Statistics Overview/11. Bayes Theorem.mp4 38.5 MB
  • 6. Working with Data Part 2/1. Merge.mp4 38.1 MB
  • 7. Working with Data Part 3/1. GroupBy on DataFrames.mp4 38.1 MB
  • 10. Machine Learning/14. Naive Bayes Part 1.mp4 37.4 MB
  • 9. Example Projects/5. Titanic Project - Part 3.mp4 36.8 MB
  • 8. Data Visualization/6. Regression Plots.mp4 36.5 MB
  • 14. Appendix Python Special Offers/1. Python Overview Part 1.mp4 36.1 MB
  • 9. Example Projects/7. Intro to Data Project - Stock Market Analysis.mp4 34.4 MB
  • 9. Example Projects/8. Data Project - Stock Market Analysis Part 1.mp4 34.0 MB
  • 12. Appendix SQL and Python/2. SQL - SELECT,DISTINCT,WHERE,AND & OR.mp4 33.9 MB
  • 4. Intro to Pandas/4. Reindex.mp4 33.8 MB
  • 2. Setup/2. IDEs and Course Resources.mp4 31.8 MB
  • 12. Appendix SQL and Python/3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions.mp4 29.5 MB
  • 3. Learning Numpy/4. Indexing Arrays.vtt 27.4 MB
  • 3. Learning Numpy/4. Indexing Arrays.mp4 27.4 MB
  • 9. Example Projects/11. Data Project - Stock Market Analysis Part 4.mp4 27.1 MB
  • 9. Example Projects/1. Data Projects Preview.mp4 27.0 MB
  • 6. Working with Data Part 2/2. Merge on Index.mp4 26.4 MB
  • 11. Appendix Statistics Overview/3. Continuous Uniform Distribution.mp4 26.4 MB
  • 5. Working with Data Part 1/1. Reading and Writing Text Files.mp4 26.0 MB
  • 4. Intro to Pandas/1. Series.mp4 26.0 MB
  • 2. Setup/1. Installation Setup and Overview.mp4 25.6 MB
  • 4. Intro to Pandas/11. Index Hierarchy.mp4 25.2 MB
  • 7. Working with Data Part 3/2. GroupBy on Dict and Series.mp4 24.4 MB
  • 7. Working with Data Part 3/4. Splitting Applying and Combining.mp4 23.2 MB
  • 11. Appendix Statistics Overview/7. Sampling Techniques.mp4 23.1 MB
  • 14. Appendix Python Special Offers/2. Python Overview Part 2.mp4 23.0 MB
  • 11. Appendix Statistics Overview/2. Discrete Uniform Distribution.mp4 22.9 MB
  • 6. Working with Data Part 2/3. Concatenate.mp4 22.2 MB
  • 8. Data Visualization/2. Histograms.mp4 21.2 MB
  • 14. Appendix Python Special Offers/3. Python Overview Part 3.mp4 20.9 MB
  • 6. Working with Data Part 2/4. Combining DataFrames.mp4 20.9 MB
  • 11. Appendix Statistics Overview/6. Normal Distribution.mp4 20.4 MB
  • 4. Intro to Pandas/10. Missing Data.mp4 19.8 MB
  • 9. Example Projects/2. Intro to Data Projects.mp4 19.6 MB
  • 8. Data Visualization/5. Box and Violin Plots.mp4 19.2 MB
  • 4. Intro to Pandas/6. Selecting Entries.mp4 19.0 MB
  • 6. Working with Data Part 2/6. Pivoting.mp4 18.8 MB
  • 4. Intro to Pandas/7. Data Alignment.mp4 18.6 MB
  • 11. Appendix Statistics Overview/8. T-Distribution.mp4 17.1 MB
  • 6. Working with Data Part 2/12. Outliers.mp4 17.0 MB
  • 11. Appendix Statistics Overview/10. Chi Square Test and Distribution.mp4 16.5 MB
  • 3. Learning Numpy/6. Universal Array Function.mp4 15.7 MB
  • 9. Example Projects/13. Data Project - Intro to Election Analysis.mp4 15.6 MB
  • 6. Working with Data Part 2/5. Reshaping.mp4 15.1 MB
  • 3. Learning Numpy/8. Array Input and Output.mp4 14.7 MB
  • 5. Working with Data Part 1/3. HTML with Python.mp4 14.1 MB
  • 1. Intro to Course and Python/1. Course Intro.mp4 13.9 MB
  • 3. Learning Numpy/2. Creating arrays.mp4 13.7 MB
  • 6. Working with Data Part 2/11. Binning.mp4 13.7 MB
  • 8. Data Visualization/4. Combining Plot Styles.mp4 12.2 MB
  • 6. Working with Data Part 2/7. Duplicates in DataFrames.mp4 11.6 MB
  • 6. Working with Data Part 2/10. Rename Index.mp4 10.6 MB
  • 4. Intro to Pandas/8. Rank and Sort.mp4 9.9 MB
  • 4. Intro to Pandas/5. Drop Entry.mp4 9.7 MB
  • 4. Intro to Pandas/3. Index objects.mp4 9.7 MB
  • 5. Working with Data Part 1/2. JSON with Python.mp4 9.4 MB
  • 7. Working with Data Part 3/5. Cross Tabulation.mp4 9.3 MB
  • 6. Working with Data Part 2/13. Permutation.mp4 9.2 MB
  • 3. Learning Numpy/3. Using arrays and scalars.mp4 8.3 MB
  • 6. Working with Data Part 2/8. Mapping.mp4 8.2 MB
  • 5. Working with Data Part 1/4. Microsoft Excel files with Python.mp4 8.0 MB
  • 3. Learning Numpy/5. Array Transposition.mp4 7.9 MB
  • 11. Appendix Statistics Overview/1. Intro to Appendix B.mp4 7.6 MB
  • 8. Data Visualization/1. Installing Seaborn.mp4 7.6 MB
  • 9. Example Projects/6. Titanic Project - Part 4.mp4 5.6 MB
  • 6. Working with Data Part 2/9. Replace.mp4 5.4 MB
  • 10. Machine Learning/16. Decision Trees and Random Forests.vtt 35.7 kB
  • 9. Example Projects/12. Data Project - Stock Market Analysis Part 5.vtt 34.0 kB
  • 8. Data Visualization/3. Kernel Density Estimate Plots.vtt 31.5 kB
  • 10. Machine Learning/5. Linear Regression Part 4.vtt 30.2 kB
  • 10. Machine Learning/13. Support Vector Machines - Part 2.vtt 29.3 kB
  • 4. Intro to Pandas/9. Summary Statistics.vtt 27.3 kB
  • 9. Example Projects/15. Data Project - Election Analysis Part 2.vtt 25.9 kB
  • 9. Example Projects/17. Data Project - Election Analysis Part 4.vtt 25.5 kB
  • 11. Appendix Statistics Overview/9. Hypothesis Testing and Confidence Intervals.vtt 24.4 kB
  • 10. Machine Learning/11. Multi Class Classification Part 2 - k Nearest Neighbor.vtt 24.2 kB
  • 10. Machine Learning/19. Natural Language Processing Part 3.vtt 23.9 kB
  • 10. Machine Learning/4. Linear Regression Part 3.vtt 23.9 kB
  • 10. Machine Learning/3. Linear Regression Part 2.vtt 23.8 kB
  • 10. Machine Learning/2. Linear Regression Part 1.vtt 23.8 kB
  • 9. Example Projects/9. Data Project - Stock Market Analysis Part 2.vtt 23.7 kB
  • 10. Machine Learning/9. Logistic Regression Part 4.vtt 23.3 kB
  • 8. Data Visualization/6. Regression Plots.vtt 23.0 kB
  • 9. Example Projects/14. Data Project - Election Analysis Part 1.vtt 22.6 kB
  • 3. Learning Numpy/7. Array Processing.vtt 22.5 kB
  • 9. Example Projects/3. Titanic Project - Part 1.vtt 22.1 kB
  • 6. Working with Data Part 2/1. Merge.vtt 21.4 kB
  • 7. Working with Data Part 3/1. GroupBy on DataFrames.vtt 20.4 kB
  • 8. Data Visualization/7. Heatmaps and Clustered Matrices.vtt 20.4 kB
  • 9. Example Projects/16. Data Project - Election Analysis Part 3.vtt 19.9 kB
  • 10. Machine Learning/10. Multi Class Classification Part 1 - Logistic Regression.vtt 19.7 kB
  • 14. Appendix Python Special Offers/1. Python Overview Part 1.vtt 19.6 kB
  • 9. Example Projects/4. Titanic Project - Part 2.vtt 19.1 kB
  • 2. Setup/3. iPythonJupyter Notebook Overview.vtt 18.1 kB
  • 11. Appendix Statistics Overview/4. Binomial Distribution.vtt 18.0 kB
  • 4. Intro to Pandas/2. DataFrames.vtt 18.0 kB
  • 10. Machine Learning/18. Natural Language Processing Part 2.vtt 17.9 kB
  • 9. Example Projects/5. Titanic Project - Part 3.vtt 17.6 kB
  • 10. Machine Learning/20. Natural Language Processing Part 4.vtt 17.5 kB
  • 10. Machine Learning/6. Logistic Regression Part 1.vtt 17.4 kB
  • 10. Machine Learning/1. Introduction to Machine Learning with SciKit Learn.vtt 17.0 kB
  • 4. Intro to Pandas/4. Reindex.vtt 16.9 kB
  • 7. Working with Data Part 3/3. Aggregation.vtt 16.9 kB
  • 13. Appendix Web Scraping with Python/1. Web Scraping Part 1.vtt 16.6 kB
  • 10. Machine Learning/12. Support Vector Machines Part 1.vtt 16.3 kB
  • 4. Intro to Pandas/11. Index Hierarchy.vtt 16.3 kB
  • 9. Example Projects/8. Data Project - Stock Market Analysis Part 1.vtt 16.0 kB
  • 10. Machine Learning/7. Logistic Regression Part 2.vtt 15.9 kB
  • 11. Appendix Statistics Overview/5. Poisson Distribution.vtt 15.9 kB
  • 4. Intro to Pandas/1. Series.vtt 15.3 kB
  • 12. Appendix SQL and Python/1. Introduction to SQL with Python.vtt 15.3 kB
  • 14. Appendix Python Special Offers/2. Python Overview Part 2.vtt 15.0 kB
  • 13. Appendix Web Scraping with Python/2. Web Scraping Part 2.vtt 14.9 kB
  • 10. Machine Learning/15. Naive Bayes Part 2.vtt 14.4 kB
  • 7. Working with Data Part 3/2. GroupBy on Dict and Series.vtt 14.2 kB
  • 12. Appendix SQL and Python/2. SQL - SELECT,DISTINCT,WHERE,AND & OR.vtt 14.1 kB
  • 9. Example Projects/10. Data Project - Stock Market Analysis Part 3.vtt 13.9 kB
  • 6. Working with Data Part 2/2. Merge on Index.vtt 13.5 kB
  • 4. Intro to Pandas/10. Missing Data.vtt 13.3 kB
  • 14. Appendix Python Special Offers/3. Python Overview Part 3.vtt 13.2 kB
  • 2. Setup/2. IDEs and Course Resources.vtt 13.0 kB
  • 10. Machine Learning/8. Logistic Regression Part 3.vtt 12.5 kB
  • 11. Appendix Statistics Overview/11. Bayes Theorem.vtt 12.5 kB
  • 5. Working with Data Part 1/1. Reading and Writing Text Files.vtt 12.2 kB
  • 10. Machine Learning/14. Naive Bayes Part 1.vtt 12.2 kB
  • 12. Appendix SQL and Python/3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions.vtt 12.1 kB
  • 6. Working with Data Part 2/4. Combining DataFrames.vtt 11.8 kB
  • 8. Data Visualization/2. Histograms.vtt 11.8 kB
  • 6. Working with Data Part 2/3. Concatenate.vtt 11.7 kB
  • 4. Intro to Pandas/7. Data Alignment.vtt 11.3 kB
  • 7. Working with Data Part 3/4. Splitting Applying and Combining.vtt 11.3 kB
  • 4. Intro to Pandas/6. Selecting Entries.vtt 10.8 kB
  • 8. Data Visualization/5. Box and Violin Plots.vtt 10.3 kB
  • 11. Appendix Statistics Overview/3. Continuous Uniform Distribution.vtt 10.0 kB
  • 10. Machine Learning/17. Natural Language Processing Part 1.vtt 9.8 kB
  • 11. Appendix Statistics Overview/2. Discrete Uniform Distribution.vtt 9.5 kB
  • 9. Example Projects/11. Data Project - Stock Market Analysis Part 4.vtt 9.0 kB
  • 3. Learning Numpy/2. Creating arrays.vtt 9.0 kB
  • 11. Appendix Statistics Overview/6. Normal Distribution.vtt 8.9 kB
  • 3. Learning Numpy/8. Array Input and Output.vtt 8.9 kB
  • 2. Setup/1. Installation Setup and Overview.vtt 8.7 kB
  • 6. Working with Data Part 2/5. Reshaping.vtt 8.4 kB
  • 6. Working with Data Part 2/6. Pivoting.vtt 8.0 kB
  • 8. Data Visualization/4. Combining Plot Styles.vtt 7.8 kB
  • 6. Working with Data Part 2/12. Outliers.vtt 7.8 kB
  • 6. Working with Data Part 2/11. Binning.vtt 7.4 kB
  • 11. Appendix Statistics Overview/8. T-Distribution.vtt 7.3 kB
  • 6. Working with Data Part 2/7. Duplicates in DataFrames.vtt 7.3 kB
  • 11. Appendix Statistics Overview/7. Sampling Techniques.vtt 7.3 kB
  • 3. Learning Numpy/6. Universal Array Function.vtt 7.2 kB
  • 1. Intro to Course and Python/2. Course FAQs.html 7.1 kB
  • 4. Intro to Pandas/8. Rank and Sort.vtt 6.9 kB
  • 9. Example Projects/2. Intro to Data Projects.vtt 6.9 kB
  • 6. Working with Data Part 2/10. Rename Index.vtt 6.8 kB
  • 4. Intro to Pandas/5. Drop Entry.vtt 6.3 kB
  • 7. Working with Data Part 3/5. Cross Tabulation.vtt 6.3 kB
  • 15. BONUS SPECIAL DISCOUNT COUPONS/1. Bonus Lecture Coupons.html 6.1 kB
  • 3. Learning Numpy/3. Using arrays and scalars.vtt 6.1 kB
  • 6. Working with Data Part 2/13. Permutation.vtt 5.9 kB
  • 4. Intro to Pandas/3. Index objects.vtt 5.4 kB
  • 5. Working with Data Part 1/2. JSON with Python.vtt 5.3 kB
  • 5. Working with Data Part 1/3. HTML with Python.vtt 5.2 kB
  • 5. Working with Data Part 1/4. Microsoft Excel files with Python.vtt 5.0 kB
  • 9. Example Projects/1. Data Projects Preview.vtt 4.9 kB
  • 9. Example Projects/7. Intro to Data Project - Stock Market Analysis.vtt 4.9 kB
  • 1. Intro to Course and Python/1. Course Intro.vtt 4.9 kB
  • 6. Working with Data Part 2/8. Mapping.vtt 4.9 kB
  • 3. Learning Numpy/5. Array Transposition.vtt 4.6 kB
  • 11. Appendix Statistics Overview/1. Intro to Appendix B.vtt 4.3 kB
  • 6. Working with Data Part 2/9. Replace.vtt 4.2 kB
  • 11. Appendix Statistics Overview/10. Chi Square Test and Distribution.vtt 3.9 kB
  • 9. Example Projects/6. Titanic Project - Part 4.vtt 3.4 kB
  • 9. Example Projects/13. Data Project - Intro to Election Analysis.vtt 3.4 kB
  • 8. Data Visualization/1. Installing Seaborn.vtt 2.5 kB
  • 3. Learning Numpy/1. Intro to numpy.html 917 Bytes
  • 9. Example Projects/2.1 First Data Project.txt 306 Bytes
  • 9. Example Projects/3.1 First Data Project.txt 306 Bytes
  • 2. Setup/3.1 Lecture 4 Info.txt 180 Bytes
  • 2. Setup/1.2 Link for FAQ.html 149 Bytes
  • 2. Setup/1.1 Link to Code Notebooks for Course!.html 131 Bytes
  • 2. Setup/2.1 Link to Code Notebooks for Course!.html 131 Bytes
  • 2. Setup/3.2 Link to Code Notebooks for Course!.html 131 Bytes
  • [Tutorialsplanet.NET].url 128 Bytes
  • 11. Appendix Statistics Overview/1.1 Viewer Link For Stats Notes.txt 121 Bytes

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