Udemy - Data Science Supervised Machine Learning in Python (11.2024)

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Udemy - Data Science Supervised Machine Learning in Python (11.2024)

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种子哈希：61547d070d399e3fb0d660d0e33d45f648ac501a
文件大小： 2.05G
已经下载：149次
下载速度：极快
收录时间：2025-07-29
最近下载：2025-10-09

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文件列表

  • 9 - Setting Up Your Environment FAQ by Student Request/43 - Anaconda Environment Setup.mp4 324.0 MB
  • 9 - Setting Up Your Environment FAQ by Student Request/44 - How to install Numpy Scipy Matplotlib and SciKit Learn.mp4 201.3 MB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/52 - Machine Learning and AI Prerequisite Roadmap pt 2.mp4 142.9 MB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/51 - Machine Learning and AI Prerequisite Roadmap pt 1.mp4 141.4 MB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/47 - Proof that using Jupyter Notebook is the same as not using it.mp4 113.7 MB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/45 - How to Code by Yourself part 1.mp4 98.1 MB
  • 1 - Introduction and Review/3 - Where to get the Code and Data.mp4 64.2 MB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/50 - Is this for Beginners or Experts Academic or Practical Fast or slowpaced.mp4 63.1 MB
  • 4 - Decision Trees/28 - Decision Tree in Code.mp4 55.1 MB
  • 3 - Naive Bayes and Bayes Classifiers/14 - Bayes Classifier Intuition Continuous.mp4 53.1 MB
  • 3 - Naive Bayes and Bayes Classifiers/16 - Naive Bayes.mp4 49.7 MB
  • 12 - Appendix FAQ Finale/54 - BONUS.mp4 45.2 MB
  • 1 - Introduction and Review/1 - Introduction and Outline.mp4 40.8 MB
  • 5 - Perceptrons/31 - Perceptron for MNIST and XOR.mp4 39.9 MB
  • 5 - Perceptrons/29 - Perceptron Concepts.mp4 39.4 MB
  • 3 - Naive Bayes and Bayes Classifiers/19 - NonNaive Bayes.mp4 37.0 MB
  • 6 - Practical Machine Learning/37 - SciKit Learn.mp4 35.2 MB
  • 3 - Naive Bayes and Bayes Classifiers/15 - Bayes Classifier Intuition Discrete.mp4 32.9 MB
  • 2 - KNearest Neighbor/7 - KNN in Code with MNIST.mp4 31.9 MB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/46 - How to Code by Yourself part 2.mp4 30.7 MB
  • 4 - Decision Trees/26 - Maximizing Information Gain.mp4 29.4 MB
  • 2 - KNearest Neighbor/13 - Suggestion Box.mp4 28.5 MB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/49 - How to Succeed in this Course Long Version.mp4 26.1 MB
  • 4 - Decision Trees/25 - Information Entropy.mp4 25.3 MB
  • 7 - Building a Machine Learning Web Service/39 - Building a Machine Learning Web Service Concepts.mp4 25.1 MB
  • 2 - KNearest Neighbor/11 - Effect of K.mp4 24.9 MB
  • 7 - Building a Machine Learning Web Service/40 - Building a Machine Learning Web Service Code.mp4 23.6 MB
  • 3 - Naive Bayes and Bayes Classifiers/21 - Linear Discriminant Analysis LDA and Quadratic Discriminant Analysis QDA.mp4 23.4 MB
  • 3 - Naive Bayes and Bayes Classifiers/18 - Naive Bayes in Code with MNIST.mp4 23.4 MB
  • 1 - Introduction and Review/4 - Review of Important Concepts.mp4 21.3 MB
  • 5 - Perceptrons/30 - Perceptron in Code.mp4 20.8 MB
  • 6 - Practical Machine Learning/38 - Regression with SciKit Learn is Easy.mp4 18.7 MB
  • 6 - Practical Machine Learning/35 - Comparison to Deep Learning.mp4 17.7 MB
  • 1 - Introduction and Review/2 - How to Succeed in this Course.mp4 17.0 MB
  • 8 - Conclusion/41 - Whats Next Support Vector Machines and Ensemble Methods eg Random Forest.mp4 15.3 MB
  • 2 - KNearest Neighbor/10 - KNN for the Donut Problem.mp4 15.3 MB
  • 4 - Decision Trees/27 - Choosing the Best Split.mp4 14.7 MB
  • 2 - KNearest Neighbor/6 - KNearest Neighbor Concepts.mp4 14.6 MB
  • 5 - Perceptrons/32 - Perceptron Loss Function.mp4 13.9 MB
  • 6 - Practical Machine Learning/34 - Feature Extraction and Feature Selection.mp4 13.9 MB
  • 9 - Setting Up Your Environment FAQ by Student Request/42 - PreInstallation Check.mp4 13.7 MB
  • 3 - Naive Bayes and Bayes Classifiers/17 - Naive Bayes Handwritten Example.mp4 13.2 MB
  • 6 - Practical Machine Learning/33 - Hyperparameters and CrossValidation.mp4 12.7 MB
  • 4 - Decision Trees/24 - Decision Tree Basics.mp4 12.6 MB
  • 2 - KNearest Neighbor/8 - When KNN Can Fail.mp4 11.7 MB
  • 4 - Decision Trees/23 - Decision Tree Intuition.mp4 11.3 MB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/48 - Python 2 vs Python 3.mp4 10.9 MB
  • 3 - Naive Bayes and Bayes Classifiers/22 - Generative vs Discriminative Models.mp4 10.1 MB
  • 2 - KNearest Neighbor/12 - KNN Exercise.mp4 9.4 MB
  • 3 - Naive Bayes and Bayes Classifiers/20 - Bayes Classifier in Code with MNIST.mp4 9.3 MB
  • 12 - Appendix FAQ Finale/53 - What is the Appendix.mp4 9.3 MB
  • 6 - Practical Machine Learning/36 - Multiclass Classification.mp4 9.3 MB
  • 2 - KNearest Neighbor/5 - KNearest Neighbor Intuition.mp4 9.3 MB
  • 2 - KNearest Neighbor/9 - KNN for the XOR Problem.mp4 7.1 MB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/subtitles/50 - Is this for Beginners or Experts Academic or Practical Fast or slowpaced Spanish.vtt 31.4 kB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/50 - Is this for Beginners or Experts Academic or Practical Fast or slowpaced.vtt 29.3 kB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/subtitles/52 - Machine Learning and AI Prerequisite Roadmap pt 2 Spanish.vtt 23.5 kB
  • 3 - Naive Bayes and Bayes Classifiers/subtitles/14 - Bayes Classifier Intuition Continuous Spanish.vtt 23.0 kB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/subtitles/45 - How to Code by Yourself part 1 Spanish.vtt 22.5 kB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/52 - Machine Learning and AI Prerequisite Roadmap pt 2.vtt 21.4 kB
  • 3 - Naive Bayes and Bayes Classifiers/14 - Bayes Classifier Intuition Continuous.vtt 21.1 kB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/45 - How to Code by Yourself part 1.vtt 20.9 kB
  • 9 - Setting Up Your Environment FAQ by Student Request/subtitles/43 - Anaconda Environment Setup Spanish.vtt 20.0 kB
  • 9 - Setting Up Your Environment FAQ by Student Request/43 - Anaconda Environment Setup.vtt 18.4 kB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/subtitles/51 - Machine Learning and AI Prerequisite Roadmap pt 1 Spanish.vtt 16.1 kB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/51 - Machine Learning and AI Prerequisite Roadmap pt 1.vtt 14.9 kB
  • 1 - Introduction and Review/subtitles/3 - Where to get the Code and Data Spanish.vtt 14.9 kB
  • 9 - Setting Up Your Environment FAQ by Student Request/subtitles/44 - How to install Numpy Scipy Matplotlib and SciKit Learn Spanish.vtt 14.3 kB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/subtitles/49 - How to Succeed in this Course Long Version Spanish.vtt 14.3 kB
  • 1 - Introduction and Review/3 - Where to get the Code and Data.vtt 14.0 kB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/subtitles/47 - Proof that using Jupyter Notebook is the same as not using it Spanish.vtt 13.9 kB
  • 1 - Introduction and Review/subtitles/1 - Introduction and Outline Spanish.vtt 13.9 kB
  • 11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/49 - How to Succeed in this Course Long Version.vtt 13.6 kB
  • 9 - Setting Up Your Environment FAQ by Student Request/44 - How to install Numpy Scipy Matplotlib and SciKit Learn.vtt 13.2 kB
  • 3 - Naive Bayes and Bayes Classifiers/subtitles/15 - Bayes Classifier Intuition Discrete Spanish.vtt 13.2 kB
  • 1 - Introduction and Review/1 - Introduction and Outline.vtt 13.0 kB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/subtitles/46 - How to Code by Yourself part 2 Spanish.vtt 13.0 kB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/47 - Proof that using Jupyter Notebook is the same as not using it.vtt 13.0 kB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/46 - How to Code by Yourself part 2.vtt 12.3 kB
  • 3 - Naive Bayes and Bayes Classifiers/15 - Bayes Classifier Intuition Discrete.vtt 11.9 kB
  • 3 - Naive Bayes and Bayes Classifiers/subtitles/16 - Naive Bayes Spanish.vtt 11.6 kB
  • 4 - Decision Trees/subtitles/28 - Decision Tree in Code Spanish.vtt 11.4 kB
  • 6 - Practical Machine Learning/subtitles/37 - SciKit Learn Spanish.vtt 11.2 kB
  • 3 - Naive Bayes and Bayes Classifiers/16 - Naive Bayes.vtt 10.6 kB
  • 6 - Practical Machine Learning/37 - SciKit Learn.vtt 10.4 kB
  • 4 - Decision Trees/28 - Decision Tree in Code.vtt 10.2 kB
  • 4 - Decision Trees/subtitles/26 - Maximizing Information Gain Spanish.vtt 9.8 kB
  • 4 - Decision Trees/26 - Maximizing Information Gain.vtt 8.9 kB
  • 5 - Perceptrons/subtitles/29 - Perceptron Concepts Spanish.vtt 8.6 kB
  • 5 - Perceptrons/29 - Perceptron Concepts.vtt 8.1 kB
  • 12 - Appendix FAQ Finale/subtitles/54 - BONUS Spanish.vtt 8.1 kB
  • 2 - KNearest Neighbor/subtitles/7 - KNN in Code with MNIST Spanish.vtt 7.6 kB
  • 7 - Building a Machine Learning Web Service/subtitles/40 - Building a Machine Learning Web Service Code Spanish.vtt 7.5 kB
  • 12 - Appendix FAQ Finale/54 - BONUS.vtt 7.5 kB
  • 3 - Naive Bayes and Bayes Classifiers/subtitles/21 - Linear Discriminant Analysis LDA and Quadratic Discriminant Analysis QDA Spanish.vtt 7.4 kB
  • 2 - KNearest Neighbor/subtitles/11 - Effect of K Spanish.vtt 7.2 kB
  • 7 - Building a Machine Learning Web Service/40 - Building a Machine Learning Web Service Code.vtt 6.9 kB
  • 3 - Naive Bayes and Bayes Classifiers/21 - Linear Discriminant Analysis LDA and Quadratic Discriminant Analysis QDA.vtt 6.9 kB
  • 2 - KNearest Neighbor/7 - KNN in Code with MNIST.vtt 6.8 kB
  • 2 - KNearest Neighbor/11 - Effect of K.vtt 6.5 kB
  • 6 - Practical Machine Learning/subtitles/35 - Comparison to Deep Learning Spanish.vtt 6.4 kB
  • 4 - Decision Trees/subtitles/24 - Decision Tree Basics Spanish.vtt 6.3 kB
  • 2 - KNearest Neighbor/subtitles/6 - KNearest Neighbor Concepts Spanish.vtt 6.3 kB
  • 9 - Setting Up Your Environment FAQ by Student Request/subtitles/42 - PreInstallation Check Spanish.vtt 6.2 kB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/subtitles/48 - Python 2 vs Python 3 Spanish.vtt 6.1 kB
  • 6 - Practical Machine Learning/subtitles/38 - Regression with SciKit Learn is Easy Spanish.vtt 6.1 kB
  • 9 - Setting Up Your Environment FAQ by Student Request/42 - PreInstallation Check.vtt 6.1 kB
  • 2 - KNearest Neighbor/6 - KNearest Neighbor Concepts.vtt 5.8 kB
  • 4 - Decision Trees/24 - Decision Tree Basics.vtt 5.7 kB
  • 4 - Decision Trees/subtitles/23 - Decision Tree Intuition Spanish.vtt 5.7 kB
  • 6 - Practical Machine Learning/35 - Comparison to Deep Learning.vtt 5.7 kB
  • 10 - Extra Help With Python Coding for Beginners FAQ by Student Request/48 - Python 2 vs Python 3.vtt 5.7 kB
  • 6 - Practical Machine Learning/38 - Regression with SciKit Learn is Easy.vtt 5.6 kB
  • 2 - KNearest Neighbor/subtitles/12 - KNN Exercise Spanish.vtt 5.4 kB
  • 7 - Building a Machine Learning Web Service/subtitles/39 - Building a Machine Learning Web Service Concepts Spanish.vtt 5.4 kB
  • 6 - Practical Machine Learning/subtitles/33 - Hyperparameters and CrossValidation Spanish.vtt 5.2 kB
  • 4 - Decision Trees/23 - Decision Tree Intuition.vtt 5.2 kB
  • 6 - Practical Machine Learning/subtitles/34 - Feature Extraction and Feature Selection Spanish.vtt 5.1 kB
  • 2 - KNearest Neighbor/12 - KNN Exercise.vtt 5.1 kB
  • 7 - Building a Machine Learning Web Service/39 - Building a Machine Learning Web Service Concepts.vtt 5.0 kB
  • 5 - Perceptrons/subtitles/32 - Perceptron Loss Function Spanish.vtt 5.0 kB
  • 3 - Naive Bayes and Bayes Classifiers/subtitles/18 - Naive Bayes in Code with MNIST Spanish.vtt 4.9 kB
  • 3 - Naive Bayes and Bayes Classifiers/subtitles/19 - NonNaive Bayes Spanish.vtt 4.9 kB
  • 5 - Perceptrons/subtitles/30 - Perceptron in Code Spanish.vtt 4.8 kB
  • 4 - Decision Trees/subtitles/27 - Choosing the Best Split Spanish.vtt 4.8 kB
  • 2 - KNearest Neighbor/subtitles/5 - KNearest Neighbor Intuition Spanish.vtt 4.8 kB
  • 6 - Practical Machine Learning/33 - Hyperparameters and CrossValidation.vtt 4.8 kB
  • 2 - KNearest Neighbor/subtitles/8 - When KNN Can Fail Spanish.vtt 4.6 kB
  • 2 - KNearest Neighbor/5 - KNearest Neighbor Intuition.vtt 4.6 kB
  • 2 - KNearest Neighbor/subtitles/13 - Suggestion Box Spanish.vtt 4.6 kB
  • 5 - Perceptrons/32 - Perceptron Loss Function.vtt 4.6 kB
  • 3 - Naive Bayes and Bayes Classifiers/19 - NonNaive Bayes.vtt 4.5 kB
  • 1 - Introduction and Review/subtitles/4 - Review of Important Concepts Spanish.vtt 4.5 kB
  • 6 - Practical Machine Learning/34 - Feature Extraction and Feature Selection.vtt 4.5 kB
  • 4 - Decision Trees/27 - Choosing the Best Split.vtt 4.4 kB
  • 3 - Naive Bayes and Bayes Classifiers/18 - Naive Bayes in Code with MNIST.vtt 4.4 kB
  • 1 - Introduction and Review/subtitles/2 - How to Succeed in this Course Spanish.vtt 4.4 kB
  • 2 - KNearest Neighbor/13 - Suggestion Box.vtt 4.4 kB
  • 5 - Perceptrons/30 - Perceptron in Code.vtt 4.3 kB
  • 4 - Decision Trees/subtitles/25 - Information Entropy Spanish.vtt 4.3 kB
  • 2 - KNearest Neighbor/8 - When KNN Can Fail.vtt 4.2 kB
  • 1 - Introduction and Review/2 - How to Succeed in this Course.vtt 4.1 kB
  • 1 - Introduction and Review/4 - Review of Important Concepts.vtt 4.1 kB
  • 6 - Practical Machine Learning/subtitles/36 - Multiclass Classification Spanish.vtt 4.0 kB
  • 4 - Decision Trees/25 - Information Entropy.vtt 4.0 kB
  • 6 - Practical Machine Learning/36 - Multiclass Classification.vtt 3.8 kB
  • 3 - Naive Bayes and Bayes Classifiers/subtitles/17 - Naive Bayes Handwritten Example Spanish.vtt 3.7 kB
  • 12 - Appendix FAQ Finale/subtitles/53 - What is the Appendix Spanish.vtt 3.6 kB
  • 8 - Conclusion/subtitles/41 - Whats Next Support Vector Machines and Ensemble Methods eg Random Forest Spanish.vtt 3.6 kB
  • 12 - Appendix FAQ Finale/53 - What is the Appendix.vtt 3.5 kB
  • 3 - Naive Bayes and Bayes Classifiers/17 - Naive Bayes Handwritten Example.vtt 3.3 kB
  • 8 - Conclusion/41 - Whats Next Support Vector Machines and Ensemble Methods eg Random Forest.vtt 3.3 kB
  • 3 - Naive Bayes and Bayes Classifiers/subtitles/22 - Generative vs Discriminative Models Spanish.vtt 3.1 kB
  • 3 - Naive Bayes and Bayes Classifiers/22 - Generative vs Discriminative Models.vtt 2.9 kB
  • 2 - KNearest Neighbor/subtitles/10 - KNN for the Donut Problem Spanish.vtt 2.6 kB
  • 2 - KNearest Neighbor/10 - KNN for the Donut Problem.vtt 2.4 kB
  • 5 - Perceptrons/subtitles/31 - Perceptron for MNIST and XOR Spanish.vtt 2.3 kB
  • 2 - KNearest Neighbor/subtitles/9 - KNN for the XOR Problem Spanish.vtt 2.2 kB
  • 5 - Perceptrons/31 - Perceptron for MNIST and XOR.vtt 2.1 kB
  • 2 - KNearest Neighbor/9 - KNN for the XOR Problem.vtt 2.0 kB
  • 3 - Naive Bayes and Bayes Classifiers/subtitles/20 - Bayes Classifier in Code with MNIST Spanish.vtt 1.6 kB
  • 3 - Naive Bayes and Bayes Classifiers/20 - Bayes Classifier in Code with MNIST.vtt 1.5 kB
  • 1 - Introduction and Review/3 - Github Link.txt 59 Bytes

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