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【压缩文件】 ChatGPT OpenAi Python

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ChatGPT OpenAi Python.rar 932.2 MB

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【影视】 [Tutorialsplanet.NET] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost

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7. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.mp4 195.4 MB
8. Extra Help With Python Coding for Beginners/3. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
3. Bootstrap Estimates and Bagging/1. Bootstrap Estimation.mp4 50.0 MB
7. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
2. Bias-Variance Trade-Off/4. Polynomial Regression Demo.mp4 43.8 MB
9/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
10. Appendix FAQ/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
9/4. What order should I take your courses in (part 2).mp4 39.5 MB
9/3. What order should I take your courses in (part 1).mp4 30.8 MB
8. Extra Help With Python Coding for Beginners/1. How to Code by Yourself (part 1).mp4 25.7 MB
3. Bootstrap Estimates and Bagging/5. Bagging Classification Trees.mp4 21.3 MB
2. Bias-Variance Trade-Off/7. Suggestion Box.mp4 16.9 MB
3. Bootstrap Estimates and Bagging/4. Bagging Regression Trees.mp4 16.6 MB
5. AdaBoost/4. AdaBoost Implementation.mp4 16.6 MB
4. Random Forest/2. Random Forest Regressor.mp4 15.6 MB
8. Extra Help With Python Coding for Beginners/2. How to Code by Yourself (part 2).mp4 15.5 MB
4. Random Forest/1. Random Forest Algorithm.mp4 15.1 MB
2. Bias-Variance Trade-Off/3. Bias-Variance Decomposition.mp4 15.0 MB
2. Bias-Variance Trade-Off/5. K-Nearest Neighbor and Decision Tree Demo.mp4 14.5 MB
9/1. How to Succeed in this Course (Long Version).mp4 13.6 MB

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【压缩文件】 [ FreeCourseWeb.com ] Beyond Basic Programming - Intermediate Python (update).zip

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[ FreeCourseWeb.com ] Beyond Basic Programming - Intermediate Python (update).zip 927.6 MB

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【压缩文件】 [ FreeCourseWeb.com ] Oreilly - Python Application Series- Python Made Simple.zip

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[ FreeCourseWeb.com ] Oreilly - Python Application Series- Python Made Simple.zip 927.2 MB

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【压缩文件】 [DesireCourse.Com] Udemy - Python 3 Image processing in Python with Photoshop CS6

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[DesireCourse.Com] Udemy - Python 3 Image processing in Python with Photoshop CS6.zip 926.6 MB
[DesireCourse.Com].txt 828 Bytes
[DesireCourse.Com].url 51 Bytes

猜你喜欢： Python Photoshop DesireCourse Image processing Udemy CS6 Com

【压缩文件】 Python 3 Image processing in Python with Photoshop CS6

收录时间:2018-11-13 文档个数:4 文档大小:926.6 MB 最近下载:2025-02-25 人气:40 磁力链接

TutsGalaxy.com.txt 41 Bytes
Torrent_downloaded_from_Demonoid_-_www.demonoid.pw_.txt 59 Bytes
Read Me.txt 80 Bytes
Python 3 Image processing in Python with Photoshop CS6.zip 926.6 MB

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【影视】 [Tutorialsplanet.NET] Udemy - Apache Spark 2.0 + Python DO Big Data Analytics & ML

收录时间:2021-05-18 文档个数:110 文档大小:926.4 MB 最近下载:2025-05-13 人气:1078 磁力链接

6. Machine Learning with Spark/6. train Linear Regression Use Case.mp4 47.0 MB
6. Machine Learning with Spark/11. train Random Forests and PCA Use Case.mp4 42.4 MB
7. APPLY Your Course Challenge Project/3. Final Solution Review - we did it !.mp4 41.7 MB
6. Machine Learning with Spark/13. Naive Bayes Classification.mp4 35.8 MB
3. Spark Programming with Python/5. train Transformations.mp4 35.0 MB
6. Machine Learning with Spark/5. Linear Regression - fit to a line.mp4 34.6 MB
6. Machine Learning with Spark/8. train Decision Trees Use Case.mp4 33.7 MB
6. Machine Learning with Spark/2. Types of Machine Learning.mp4 30.5 MB
2. Introduction to Apache Spark/2. train Setup your Spark Python environment.mp4 29.0 MB
5. Spark Streaming/3. train Spark Streaming.mp4 28.5 MB
4. Spark SQL/2. train SQL Data Frames.mp4 27.3 MB
6. Machine Learning with Spark/12. Text Pre-processing with TF-IDF.mp4 27.2 MB
6. Machine Learning with Spark/3. Analyzing results and Errors.mp4 25.0 MB
6. Machine Learning with Spark/16. train K-Means Clustering Use Case.mp4 23.6 MB
6. Machine Learning with Spark/17. Recommendation Engines.mp4 21.6 MB
6. Machine Learning with Spark/15. K-Means Clustering - grouping similar items.mp4 21.6 MB
6. Machine Learning with Spark/1. Types of Analytics - simple to predictive.mp4 21.5 MB
6. Machine Learning with Spark/14. train Naive Bayes and Text Pre-processing Use Case.mp4 20.8 MB
3. Spark Programming with Python/8. train Actions.mp4 19.6 MB
2. Introduction to Apache Spark/6. Spark Architecture - How it all works..mp4 19.6 MB

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【影视】 [FreeCourseLab.com] Udemy - Apache Spark 2.0 + Python DO Big Data Analytics & ML

收录时间:2021-03-31 文档个数:110 文档大小:926.4 MB 最近下载:2025-01-10 人气:152 磁力链接

6. Machine Learning with Spark/6. train Linear Regression Use Case.mp4 47.0 MB
6. Machine Learning with Spark/11. train Random Forests and PCA Use Case.mp4 42.4 MB
7. APPLY Your Course Challenge Project/3. Final Solution Review - we did it !.mp4 41.7 MB
6. Machine Learning with Spark/13. Naive Bayes Classification.mp4 35.8 MB
3. Spark Programming with Python/5. train Transformations.mp4 35.0 MB
6. Machine Learning with Spark/5. Linear Regression - fit to a line.mp4 34.6 MB
6. Machine Learning with Spark/8. train Decision Trees Use Case.mp4 33.7 MB
6. Machine Learning with Spark/2. Types of Machine Learning.mp4 30.5 MB
2. Introduction to Apache Spark/2. train Setup your Spark Python environment.mp4 29.0 MB
5. Spark Streaming/3. train Spark Streaming.mp4 28.5 MB
4. Spark SQL/2. train SQL Data Frames.mp4 27.3 MB
6. Machine Learning with Spark/12. Text Pre-processing with TF-IDF.mp4 27.2 MB
6. Machine Learning with Spark/3. Analyzing results and Errors.mp4 25.0 MB
6. Machine Learning with Spark/16. train K-Means Clustering Use Case.mp4 23.6 MB
6. Machine Learning with Spark/17. Recommendation Engines.mp4 21.6 MB
6. Machine Learning with Spark/15. K-Means Clustering - grouping similar items.mp4 21.6 MB
6. Machine Learning with Spark/1. Types of Analytics - simple to predictive.mp4 21.5 MB
6. Machine Learning with Spark/14. train Naive Bayes and Text Pre-processing Use Case.mp4 20.8 MB
3. Spark Programming with Python/8. train Actions.mp4 19.6 MB
2. Introduction to Apache Spark/6. Spark Architecture - How it all works..mp4 19.6 MB

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【影视】 Boa.vs.Python.2004.WEBRip.x264-ION10

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Boa.vs.Python.2004.WEBRip.x264-ION10.mp4 925.9 MB
Subs/2_English.srt 95.5 kB
RARBG_DO_NOT_MIRROR.exe 99 Bytes
RARBG.txt 30 Bytes

猜你喜欢： ION10 Python WEBRip vs 2004 x264 Boa

【影视】 Boa.vs.Python.2004.WEBRip.x264-ION10

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Boa.vs.Python.2004.WEBRip.x264-ION10.mp4 925.9 MB

猜你喜欢： ION10 Python WEBRip vs 2004 x264 Boa

【影视】 [FreeCoursesOnline.Me] TalkPython - Visual Studio Code for Python Developers

收录时间:2024-05-11 文档个数:53 文档大小:925.5 MB 最近下载:2025-05-15 人气:3114 磁力链接

47. Working with a Git Repository.mp4 67.8 MB
16. Extensions.mp4 54.4 MB
15. Common Shortcuts.mp4 50.3 MB
05. Choosing Your Python Distribution.mp4 49.0 MB
23. Linting and Formatting Code.mp4 40.7 MB
01. Welcome to the Course.mp4 36.6 MB
48. Viewing and Syncing Changes.mp4 32.4 MB
17. Themes.mp4 31.6 MB
46. What is Source Control and Why Do You Need It.mp4 30.8 MB
51. Thank you, Summary and Resources.mp4 29.3 MB
06. Installing VS Code (There Are Choices).mp4 28.1 MB
49. The GitHub PR (Pull Request) Extension.mp4 27.4 MB
02. What You'll Need.mp4 26.8 MB
34. Command-line Debugging Techniques.mp4 25.2 MB
37. Working with Debug Configurations.mp4 20.7 MB
10. Command Palette.mp4 19.1 MB
24. Refactoring Code with VS Code.mp4 19.1 MB
28. Handling multiple Python Versions with pyenv.mp4 18.9 MB
35. Debugging with Visual Studio Code.mp4 18.8 MB
25. Code Snippets.mp4 17.3 MB

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【影视】 TalkPython - Visual Studio Code for Python Developers

收录时间:2025-04-28 文档个数:53 文档大小:925.5 MB 最近下载:2025-05-15 人气:17 磁力链接

47. Working with a Git Repository.mp4 67.8 MB
16. Extensions.mp4 54.4 MB
15. Common Shortcuts.mp4 50.3 MB
05. Choosing Your Python Distribution.mp4 49.0 MB
23. Linting and Formatting Code.mp4 40.7 MB
01. Welcome to the Course.mp4 36.6 MB
48. Viewing and Syncing Changes.mp4 32.4 MB
17. Themes.mp4 31.6 MB
46. What is Source Control and Why Do You Need It.mp4 30.8 MB
51. Thank you, Summary and Resources.mp4 29.3 MB
06. Installing VS Code (There Are Choices).mp4 28.1 MB
49. The GitHub PR (Pull Request) Extension.mp4 27.4 MB
02. What You'll Need.mp4 26.8 MB
34. Command-line Debugging Techniques.mp4 25.2 MB
37. Working with Debug Configurations.mp4 20.7 MB
10. Command Palette.mp4 19.1 MB
24. Refactoring Code with VS Code.mp4 19.1 MB
28. Handling multiple Python Versions with pyenv.mp4 18.9 MB
35. Debugging with Visual Studio Code.mp4 18.8 MB
25. Code Snippets.mp4 17.3 MB

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【影视】 [FreeCourseSite.com] Udemy - Cluster Analysis and Unsupervised Machine Learning in Python

收录时间:2021-03-17 文档个数:80 文档大小:924.3 MB 最近下载:2025-05-09 人气:1505 磁力链接

5. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
5. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt 82.1 MB
5. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
5. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
5. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
5. Appendix/11. What order should I take your courses in (part 2).mp4 39.5 MB
3. Hierarchical Clustering/5. Application Donald Trump vs. Hillary Clinton Tweets.mp4 37.0 MB
2. K-Means Clustering/5. Soft K-Means in Python Code.mp4 31.7 MB
4. Gaussian Mixture Models (GMMs)/3. Write a Gaussian Mixture Model in Python Code.mp4 31.6 MB
5. Appendix/10. What order should I take your courses in (part 1).mp4 30.8 MB
3. Hierarchical Clustering/4. Application Evolution.mp4 27.7 MB
2. K-Means Clustering/12. K-Means Application Finding Clusters of Related Words.mp4 27.2 MB
2. K-Means Clustering/3. Soft K-Means.mp4 26.5 MB
5. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
5. Appendix/6. How to Succeed in this Course (Long Version).mp4 19.2 MB
2. K-Means Clustering/7. Examples of where K-Means can fail.mp4 17.8 MB
5. Appendix/5. How to Code by Yourself (part 2).mp4 15.5 MB
2. K-Means Clustering/1. An Easy Introduction to K-Means Clustering.mp4 13.2 MB
3. Hierarchical Clustering/3. Using Hierarchical Clustering in Python and Interpreting the Dendrogram.mp4 12.4 MB
2. K-Means Clustering/9. How to Evaluate a Clustering (Purity, Davies-Bouldin Index).mp4 11.9 MB

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【影视】 [DesireCourse.Net] Udemy - Cluster Analysis and Unsupervised Machine Learning in Python

收录时间:2022-01-18 文档个数:80 文档大小:924.3 MB 最近下载:2025-05-13 人气:813 磁力链接

5. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
5. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt 82.1 MB
5. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
5. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
5. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
5. Appendix/11. What order should I take your courses in (part 2).mp4 39.5 MB
3. Hierarchical Clustering/5. Application Donald Trump vs. Hillary Clinton Tweets.mp4 37.0 MB
2. K-Means Clustering/5. Soft K-Means in Python Code.mp4 31.7 MB
4. Gaussian Mixture Models (GMMs)/3. Write a Gaussian Mixture Model in Python Code.mp4 31.6 MB
5. Appendix/10. What order should I take your courses in (part 1).mp4 30.8 MB
3. Hierarchical Clustering/4. Application Evolution.mp4 27.7 MB
2. K-Means Clustering/12. K-Means Application Finding Clusters of Related Words.mp4 27.2 MB
2. K-Means Clustering/3. Soft K-Means.mp4 26.5 MB
5. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
5. Appendix/6. How to Succeed in this Course (Long Version).mp4 19.2 MB
2. K-Means Clustering/7. Examples of where K-Means can fail.mp4 17.8 MB
5. Appendix/5. How to Code by Yourself (part 2).mp4 15.5 MB
2. K-Means Clustering/1. An Easy Introduction to K-Means Clustering.mp4 13.2 MB
3. Hierarchical Clustering/3. Using Hierarchical Clustering in Python and Interpreting the Dendrogram.mp4 12.4 MB
2. K-Means Clustering/9. How to Evaluate a Clustering (Purity, Davies-Bouldin Index).mp4 11.9 MB

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【影视】 [FreeCoursesOnline.Me] [Coursera] Applied Machine Learning in Python - [FCO]

收录时间:2021-03-10 文档个数:76 文档大小:924.2 MB 最近下载:2025-05-13 人气:1700 磁力链接

003.Module 3 Evaluation/019. Model Evaluation & Selection.mp4 48.3 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/002. Key Concepts in Machine Learning.mp4 46.7 MB
004.Module 4 Supervised Machine Learning - Part 2/029. Neural Networks.mp4 43.5 MB
002.Module 2 Supervised Machine Learning/012. Linear Regression Ridge, Lasso, and Polynomial Regression.mp4 41.9 MB
002.Module 2 Supervised Machine Learning/016. Kernelized Support Vector Machines.mp4 41.0 MB
002.Module 2 Supervised Machine Learning/007. Introduction to Supervised Machine Learning.mp4 39.7 MB
002.Module 2 Supervised Machine Learning/018. Decision Trees.mp4 39.7 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/006. K-Nearest Neighbors Classification.mp4 38.0 MB
003.Module 3 Evaluation/025. Model Selection Optimizing Classifiers for Different Evaluation Metrics.mp4 36.2 MB
004.Module 4 Supervised Machine Learning - Part 2/031. Data Leakage.mp4 34.5 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/005. Examining the Data.mp4 33.8 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/004. An Example Machine Learning Problem.mp4 33.3 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/001. Introduction.mp4 32.6 MB
002.Module 2 Supervised Machine Learning/011. Linear Regression Least-Squares.mp4 31.5 MB
005.Optional Unsupervised Machine Learning/034. Clustering.mp4 28.5 MB
004.Module 4 Supervised Machine Learning - Part 2/027. Random Forests.mp4 27.7 MB
002.Module 2 Supervised Machine Learning/014. Linear Classifiers Support Vector Machines.mp4 23.8 MB
002.Module 2 Supervised Machine Learning/010. K-Nearest Neighbors Classification and Regression.mp4 23.6 MB
004.Module 4 Supervised Machine Learning - Part 2/026. Naive Bayes Classifiers.mp4 22.4 MB
003.Module 3 Evaluation/020. Confusion Matrices & Basic Evaluation Metrics.mp4 21.8 MB

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【影视】 [FreeCoursesOnline.Me] Coursera - Applied Machine Learning in Python

收录时间:2018-08-25 文档个数:73 文档大小:923.9 MB 最近下载:2025-05-16 人气:3741 磁力链接

001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/001. Introduction.mp4 32.6 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/001. Introduction.srt 16.5 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/002. Key Concepts in Machine Learning.mp4 46.7 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/002. Key Concepts in Machine Learning.srt 19.3 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/003. Python Tools for Machine Learning.mp4 13.5 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/003. Python Tools for Machine Learning.srt 6.3 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/004. An Example Machine Learning Problem.mp4 33.3 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/004. An Example Machine Learning Problem.srt 15.2 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/005. Examining the Data.mp4 33.8 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/005. Examining the Data.srt 12.3 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/006. K-Nearest Neighbors Classification.mp4 38.0 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/006. K-Nearest Neighbors Classification.srt 26.8 kB
002.Module 2 Supervised Machine Learning/007. Introduction to Supervised Machine Learning.mp4 39.7 MB
002.Module 2 Supervised Machine Learning/007. Introduction to Supervised Machine Learning.srt 22.7 kB
002.Module 2 Supervised Machine Learning/008. Overfitting and Underfitting.mp4 20.5 MB
002.Module 2 Supervised Machine Learning/008. Overfitting and Underfitting.srt 16.2 kB
002.Module 2 Supervised Machine Learning/009. Supervised Learning Datasets.mp4 11.8 MB
002.Module 2 Supervised Machine Learning/009. Supervised Learning Datasets.srt 6.9 kB
002.Module 2 Supervised Machine Learning/010. K-Nearest Neighbors Classification and Regression.mp4 23.6 MB
002.Module 2 Supervised Machine Learning/010. K-Nearest Neighbors Classification and Regression.srt 17.5 kB

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