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[DesireCourse.Net] Udemy - Learning Python for Data Analysis and Visualization

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[DesireCourse.Net] Udemy - Learning Python for Data Analysis and Visualization

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种子哈希:5cefb9790d82c33d315fb2dec6609a475838f368
文件大小: 1.93G
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收录时间:2021-03-19
最近下载:2025-08-03

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文件列表

  • 10. Machine Learning/16. Decision Trees and Random Forests.mp4 160.4 MB
  • 10. Machine Learning/19. Natural Language Processing Part 3.mp4 97.0 MB
  • 9. Example Projects/17. Data Project - Election Analysis Part 4.mp4 86.1 MB
  • 10. Machine Learning/20. Natural Language Processing Part 4.mp4 70.4 MB
  • 10. Machine Learning/18. Natural Language Processing Part 2.mp4 62.6 MB
  • 10. Machine Learning/17. Natural Language Processing Part 1.mp4 46.0 MB
  • 2. Setup/3. iPythonJupyter Notebook Overview.mp4 41.4 MB
  • 9. Example Projects/12. Data Project - Stock Market Analysis Part 5.mp4 38.6 MB
  • 10. Machine Learning/13. Support Vector Machines - Part 2.mp4 37.7 MB
  • 10. Machine Learning/9. Logistic Regression Part 4.mp4 37.0 MB
  • 10. Machine Learning/5. Linear Regression Part 4.mp4 32.4 MB
  • 11. Appendix Statistics Overview/9. Hypothesis Testing and Confidence Intervals.mp4 32.2 MB
  • 10. Machine Learning/11. Multi Class Classification Part 2 - k Nearest Neighbor.mp4 32.1 MB
  • 2. Setup/2. IDEs and Course Resources.mp4 31.8 MB
  • 10. Machine Learning/4. Linear Regression Part 3.mp4 28.5 MB
  • 8. Data Visualization/3. Kernel Density Estimate Plots.mp4 28.4 MB
  • 10. Machine Learning/10. Multi Class Classification Part 1 - Logistic Regression.mp4 28.1 MB
  • 9. Example Projects/1. Data Projects Preview.mp4 27.1 MB
  • 10. Machine Learning/6. Logistic Regression Part 1.mp4 26.2 MB
  • 9. Example Projects/15. Data Project - Election Analysis Part 2.mp4 26.1 MB
  • 2. Setup/1. Installation Setup and Overview.mp4 25.5 MB
  • 10. Machine Learning/2. Linear Regression Part 1.mp4 25.3 MB
  • 10. Machine Learning/12. Support Vector Machines Part 1.mp4 24.7 MB
  • 9. Example Projects/9. Data Project - Stock Market Analysis Part 2.mp4 24.6 MB
  • 10. Machine Learning/15. Naive Bayes Part 2.mp4 24.4 MB
  • 10. Machine Learning/3. Linear Regression Part 2.mp4 23.6 MB
  • 4. Intro to Pandas/9. Summary Statistics.mp4 23.0 MB
  • 4. Intro to Pandas/2. DataFrames.mp4 22.9 MB
  • 10. Machine Learning/7. Logistic Regression Part 2.mp4 21.8 MB
  • 3. Learning Numpy/7. Array Processing.mp4 21.5 MB
  • 9. Example Projects/14. Data Project - Election Analysis Part 1.mp4 20.3 MB
  • 9. Example Projects/3. Titanic Project - Part 1.mp4 19.7 MB
  • 7. Working with Data Part 3/3. Aggregation.mp4 19.6 MB
  • 6. Working with Data Part 2/1. Merge.mp4 19.5 MB
  • 8. Data Visualization/7. Heatmaps and Clustered Matrices.mp4 19.1 MB
  • 10. Machine Learning/1. Introduction to Machine Learning with SciKit Learn.mp4 18.8 MB
  • 9. Example Projects/4. Titanic Project - Part 2.mp4 18.4 MB
  • 8. Data Visualization/6. Regression Plots.mp4 18.3 MB
  • 14. Appendix Python Special Offers/1. Python Overview Part 1.mp4 18.2 MB
  • 13. Appendix Web Scraping with Python/2. Web Scraping Part 2.mp4 18.2 MB
  • 7. Working with Data Part 3/1. GroupBy on DataFrames.mp4 18.0 MB
  • 9. Example Projects/16. Data Project - Election Analysis Part 3.srt 17.9 MB
  • 9. Example Projects/16. Data Project - Election Analysis Part 3.mp4 17.9 MB
  • 11. Appendix Statistics Overview/4. Binomial Distribution.mp4 17.8 MB
  • 9. Example Projects/10. Data Project - Stock Market Analysis Part 3.mp4 17.4 MB
  • 10. Machine Learning/8. Logistic Regression Part 3.mp4 17.3 MB
  • 12. Appendix SQL and Python/1. Introduction to SQL with Python.mp4 17.2 MB
  • 9. Example Projects/5. Titanic Project - Part 3.mp4 17.0 MB
  • 11. Appendix Statistics Overview/5. Poisson Distribution.mp4 16.8 MB
  • 4. Intro to Pandas/4. Reindex.mp4 16.6 MB
  • 9. Example Projects/13. Data Project - Intro to Election Analysis.mp4 15.6 MB
  • 13. Appendix Web Scraping with Python/1. Web Scraping Part 1.mp4 15.3 MB
  • 11. Appendix Statistics Overview/11. Bayes Theorem.mp4 15.2 MB
  • 10. Machine Learning/14. Naive Bayes Part 1.mp4 14.7 MB
  • 9. Example Projects/8. Data Project - Stock Market Analysis Part 1.mp4 14.3 MB
  • 12. Appendix SQL and Python/2. SQL - SELECT,DISTINCT,WHERE,AND & OR.mp4 14.1 MB
  • 3. Learning Numpy/4. Indexing Arrays.mp4 13.9 MB
  • 4. Intro to Pandas/1. Series.mp4 13.2 MB
  • 6. Working with Data Part 2/2. Merge on Index.mp4 12.9 MB
  • 4. Intro to Pandas/11. Index Hierarchy.mp4 12.8 MB
  • 7. Working with Data Part 3/2. GroupBy on Dict and Series.mp4 12.4 MB
  • 12. Appendix SQL and Python/3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions.mp4 12.3 MB
  • 14. Appendix Python Special Offers/2. Python Overview Part 2.mp4 11.6 MB
  • 7. Working with Data Part 3/4. Splitting Applying and Combining.mp4 11.1 MB
  • 5. Working with Data Part 1/1. Reading and Writing Text Files.mp4 10.9 MB
  • 9. Example Projects/7. Intro to Data Project - Stock Market Analysis.mp4 10.9 MB
  • 4. Intro to Pandas/10. Missing Data.mp4 10.4 MB
  • 11. Appendix Statistics Overview/3. Continuous Uniform Distribution.mp4 10.4 MB
  • 14. Appendix Python Special Offers/3. Python Overview Part 3.mp4 10.3 MB
  • 9. Example Projects/11. Data Project - Stock Market Analysis Part 4.mp4 10.3 MB
  • 6. Working with Data Part 2/3. Concatenate.mp4 10.2 MB
  • 6. Working with Data Part 2/4. Combining DataFrames.mp4 10.1 MB
  • 4. Intro to Pandas/6. Selecting Entries.mp4 10.0 MB
  • 4. Intro to Pandas/7. Data Alignment.mp4 10.0 MB
  • 8. Data Visualization/2. Histograms.mp4 9.8 MB
  • 8. Data Visualization/5. Box and Violin Plots.mp4 9.1 MB
  • 11. Appendix Statistics Overview/2. Discrete Uniform Distribution.mp4 9.1 MB
  • 11. Appendix Statistics Overview/6. Normal Distribution.mp4 8.7 MB
  • 11. Appendix Statistics Overview/7. Sampling Techniques.mp4 8.5 MB
  • 6. Working with Data Part 2/12. Outliers.mp4 7.9 MB
  • 6. Working with Data Part 2/6. Pivoting.mp4 7.5 MB
  • 6. Working with Data Part 2/5. Reshaping.mp4 7.5 MB
  • 3. Learning Numpy/8. Array Input and Output.mp4 7.4 MB
  • 3. Learning Numpy/2. Creating arrays.mp4 7.0 MB
  • 9. Example Projects/2. Intro to Data Projects.mp4 7.0 MB
  • 11. Appendix Statistics Overview/8. T-Distribution.mp4 7.0 MB
  • 3. Learning Numpy/6. Universal Array Function.mp4 6.7 MB
  • 6. Working with Data Part 2/11. Binning.mp4 6.6 MB
  • 1. Intro to Course and Python/1. Course Intro.mp4 6.2 MB
  • 8. Data Visualization/4. Combining Plot Styles.mp4 6.0 MB
  • 5. Working with Data Part 1/3. HTML with Python.mp4 6.0 MB
  • 11. Appendix Statistics Overview/10. Chi Square Test and Distribution.mp4 5.9 MB
  • 6. Working with Data Part 2/7. Duplicates in DataFrames.mp4 5.7 MB
  • 6. Working with Data Part 2/10. Rename Index.mp4 5.5 MB
  • 4. Intro to Pandas/5. Drop Entry.mp4 5.3 MB
  • 4. Intro to Pandas/8. Rank and Sort.mp4 5.1 MB
  • 4. Intro to Pandas/3. Index objects.mp4 4.8 MB
  • 6. Working with Data Part 2/13. Permutation.mp4 4.8 MB
  • 7. Working with Data Part 3/5. Cross Tabulation.mp4 4.7 MB
  • 5. Working with Data Part 1/2. JSON with Python.mp4 4.5 MB
  • 3. Learning Numpy/3. Using arrays and scalars.mp4 4.3 MB
  • 6. Working with Data Part 2/8. Mapping.mp4 4.1 MB
  • 3. Learning Numpy/5. Array Transposition.mp4 3.9 MB
  • 5. Working with Data Part 1/4. Microsoft Excel files with Python.mp4 3.8 MB
  • 11. Appendix Statistics Overview/1. Intro to Appendix B.mp4 3.1 MB
  • 6. Working with Data Part 2/9. Replace.mp4 2.8 MB
  • 9. Example Projects/6. Titanic Project - Part 4.mp4 2.6 MB
  • 8. Data Visualization/1. Installing Seaborn.mp4 2.5 MB
  • 10. Machine Learning/16. Decision Trees and Random Forests.srt 43.8 kB
  • 9. Example Projects/12. Data Project - Stock Market Analysis Part 5.srt 37.5 kB
  • 10. Machine Learning/13. Support Vector Machines - Part 2.srt 36.2 kB
  • 8. Data Visualization/3. Kernel Density Estimate Plots.srt 34.7 kB
  • 10. Machine Learning/5. Linear Regression Part 4.srt 33.2 kB
  • 9. Example Projects/17. Data Project - Election Analysis Part 4.srt 31.2 kB
  • 4. Intro to Pandas/9. Summary Statistics.srt 30.1 kB
  • 10. Machine Learning/11. Multi Class Classification Part 2 - k Nearest Neighbor.srt 29.8 kB
  • 10. Machine Learning/19. Natural Language Processing Part 3.srt 29.3 kB
  • 11. Appendix Statistics Overview/9. Hypothesis Testing and Confidence Intervals.srt 29.0 kB
  • 9. Example Projects/15. Data Project - Election Analysis Part 2.srt 28.5 kB
  • 10. Machine Learning/9. Logistic Regression Part 4.srt 28.3 kB
  • 10. Machine Learning/4. Linear Regression Part 3.srt 26.3 kB
  • 10. Machine Learning/3. Linear Regression Part 2.srt 26.2 kB
  • 10. Machine Learning/2. Linear Regression Part 1.srt 26.2 kB
  • 9. Example Projects/9. Data Project - Stock Market Analysis Part 2.srt 26.1 kB
  • 8. Data Visualization/6. Regression Plots.srt 25.5 kB
  • 14. Appendix Python Special Offers/1. Python Overview Part 1.srt 25.4 kB
  • 3. Learning Numpy/7. Array Processing.srt 24.9 kB
  • 9. Example Projects/14. Data Project - Election Analysis Part 1.srt 24.9 kB
  • 10. Machine Learning/10. Multi Class Classification Part 1 - Logistic Regression.srt 24.5 kB
  • 9. Example Projects/3. Titanic Project - Part 1.srt 24.4 kB
  • 6. Working with Data Part 2/1. Merge.srt 23.6 kB
  • 2. Setup/3. iPythonJupyter Notebook Overview.srt 23.2 kB
  • 7. Working with Data Part 3/1. GroupBy on DataFrames.srt 22.7 kB
  • 8. Data Visualization/7. Heatmaps and Clustered Matrices.srt 22.6 kB
  • 4. Intro to Pandas/2. DataFrames.srt 22.5 kB
  • 10. Machine Learning/18. Natural Language Processing Part 2.srt 22.1 kB
  • 10. Machine Learning/20. Natural Language Processing Part 4.srt 21.5 kB
  • 9. Example Projects/4. Titanic Project - Part 2.srt 21.0 kB
  • 10. Machine Learning/6. Logistic Regression Part 1.srt 20.7 kB
  • 10. Machine Learning/1. Introduction to Machine Learning with SciKit Learn.srt 20.2 kB
  • 11. Appendix Statistics Overview/4. Binomial Distribution.srt 19.8 kB
  • 10. Machine Learning/7. Logistic Regression Part 2.srt 19.8 kB
  • 10. Machine Learning/12. Support Vector Machines Part 1.srt 19.5 kB
  • 9. Example Projects/5. Titanic Project - Part 3.srt 19.3 kB
  • 3. Learning Numpy/4. Indexing Arrays.srt 19.2 kB
  • 4. Intro to Pandas/4. Reindex.srt 18.7 kB
  • 7. Working with Data Part 3/3. Aggregation.srt 18.6 kB
  • 13. Appendix Web Scraping with Python/1. Web Scraping Part 1.srt 18.2 kB
  • 4. Intro to Pandas/11. Index Hierarchy.srt 17.9 kB
  • 9. Example Projects/8. Data Project - Stock Market Analysis Part 1.srt 17.7 kB
  • 11. Appendix Statistics Overview/5. Poisson Distribution.srt 17.5 kB
  • 10. Machine Learning/15. Naive Bayes Part 2.srt 17.2 kB
  • 4. Intro to Pandas/1. Series.srt 16.9 kB
  • 12. Appendix SQL and Python/1. Introduction to SQL with Python.srt 16.8 kB
  • 14. Appendix Python Special Offers/2. Python Overview Part 2.srt 16.6 kB
  • 2. Setup/2. IDEs and Course Resources.srt 16.6 kB
  • 13. Appendix Web Scraping with Python/2. Web Scraping Part 2.srt 16.5 kB
  • 7. Working with Data Part 3/2. GroupBy on Dict and Series.srt 15.7 kB
  • 12. Appendix SQL and Python/2. SQL - SELECT,DISTINCT,WHERE,AND & OR.srt 15.4 kB
  • 9. Example Projects/10. Data Project - Stock Market Analysis Part 3.srt 15.3 kB
  • 10. Machine Learning/8. Logistic Regression Part 3.srt 15.2 kB
  • 6. Working with Data Part 2/2. Merge on Index.srt 14.9 kB
  • 4. Intro to Pandas/10. Missing Data.srt 14.7 kB
  • 11. Appendix Statistics Overview/11. Bayes Theorem.srt 14.7 kB
  • 14. Appendix Python Special Offers/3. Python Overview Part 3.srt 14.5 kB
  • 10. Machine Learning/14. Naive Bayes Part 1.srt 14.1 kB
  • 5. Working with Data Part 1/1. Reading and Writing Text Files.srt 13.4 kB
  • 12. Appendix SQL and Python/3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions.srt 13.2 kB
  • 6. Working with Data Part 2/4. Combining DataFrames.srt 13.1 kB
  • 8. Data Visualization/2. Histograms.srt 12.9 kB
  • 6. Working with Data Part 2/3. Concatenate.srt 12.9 kB
  • 4. Intro to Pandas/7. Data Alignment.srt 12.5 kB
  • 7. Working with Data Part 3/4. Splitting Applying and Combining.srt 12.4 kB
  • 4. Intro to Pandas/6. Selecting Entries.srt 12.0 kB
  • 8. Data Visualization/5. Box and Violin Plots.srt 11.3 kB
  • 10. Machine Learning/17. Natural Language Processing Part 1.srt 11.2 kB
  • 11. Appendix Statistics Overview/3. Continuous Uniform Distribution.srt 11.0 kB
  • 2. Setup/1. Installation Setup and Overview.srt 10.5 kB
  • 11. Appendix Statistics Overview/2. Discrete Uniform Distribution.srt 10.4 kB
  • 9. Example Projects/11. Data Project - Stock Market Analysis Part 4.srt 9.9 kB
  • 3. Learning Numpy/2. Creating arrays.srt 9.8 kB
  • 3. Learning Numpy/8. Array Input and Output.srt 9.8 kB
  • 11. Appendix Statistics Overview/6. Normal Distribution.srt 9.7 kB
  • 6. Working with Data Part 2/5. Reshaping.srt 9.2 kB
  • 6. Working with Data Part 2/6. Pivoting.srt 8.7 kB
  • 8. Data Visualization/4. Combining Plot Styles.srt 8.6 kB
  • 6. Working with Data Part 2/12. Outliers.srt 8.5 kB
  • 6. Working with Data Part 2/11. Binning.srt 8.1 kB
  • 11. Appendix Statistics Overview/8. T-Distribution.srt 8.0 kB
  • 6. Working with Data Part 2/7. Duplicates in DataFrames.srt 7.9 kB
  • 11. Appendix Statistics Overview/7. Sampling Techniques.srt 7.9 kB
  • 3. Learning Numpy/6. Universal Array Function.srt 7.9 kB
  • 4. Intro to Pandas/8. Rank and Sort.srt 7.6 kB
  • 9. Example Projects/2. Intro to Data Projects.srt 7.5 kB
  • 6. Working with Data Part 2/10. Rename Index.srt 7.5 kB
  • 1. Intro to Course and Python/2. Course FAQs.html 7.1 kB
  • 4. Intro to Pandas/5. Drop Entry.srt 6.9 kB
  • 7. Working with Data Part 3/5. Cross Tabulation.srt 6.9 kB
  • 6. Working with Data Part 2/13. Permutation.srt 6.8 kB
  • 3. Learning Numpy/3. Using arrays and scalars.srt 6.7 kB
  • 4. Intro to Pandas/3. Index objects.srt 5.9 kB
  • 1. Intro to Course and Python/1. Course Intro.srt 5.9 kB
  • 5. Working with Data Part 1/2. JSON with Python.srt 5.8 kB
  • 5. Working with Data Part 1/3. HTML with Python.srt 5.7 kB
  • 5. Working with Data Part 1/4. Microsoft Excel files with Python.srt 5.4 kB
  • 9. Example Projects/1. Data Projects Preview.srt 5.4 kB
  • 9. Example Projects/7. Intro to Data Project - Stock Market Analysis.srt 5.3 kB
  • 6. Working with Data Part 2/8. Mapping.srt 5.3 kB
  • 3. Learning Numpy/5. Array Transposition.srt 5.1 kB
  • 11. Appendix Statistics Overview/1. Intro to Appendix B.srt 4.7 kB
  • 6. Working with Data Part 2/9. Replace.srt 4.6 kB
  • 11. Appendix Statistics Overview/10. Chi Square Test and Distribution.srt 4.4 kB
  • 9. Example Projects/6. Titanic Project - Part 4.srt 3.7 kB
  • 9. Example Projects/13. Data Project - Intro to Election Analysis.srt 3.7 kB
  • 8. Data Visualization/1. Installing Seaborn.srt 2.7 kB
  • 3. Learning Numpy/1. Intro to numpy.html 917 Bytes
  • 15. BONUS SECTION THANK YOU!/1. Bonus Lecture.html 532 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/1.1 Link for FAQ.html 149 Bytes
  • 2. Setup/1.2 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
  • 11. Appendix Statistics Overview/1.1 Viewer Link For Stats Notes.txt 121 Bytes
  • [FreeCourseWorld.Com].url 54 Bytes
  • [DesireCourse.Net].url 51 Bytes
  • [CourseClub.Me].url 48 Bytes

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