Udemy - Cluster Analysis and Unsupervised Machine Learning in Python [Desire Course]

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[DesireCourse.Net] Udemy - Cluster Analysis and Unsupervised Machine Learning in Python 1. Introduction to Unsupervised Learning
  • 1. Introduction and Outline.mp4 (4.1 MB)
  • 1. Introduction and Outline.vtt (3.2 KB)
  • 2. What is unsupervised learning used for.mp4 (7.6 MB)
  • 2. What is unsupervised learning used for.vtt (5.3 KB)
  • 3. Why Use Clustering.mp4 (6.6 MB)
  • 3. Why Use Clustering.vtt (5.2 KB)
  • 4. How to Succeed in this Course.mp4 (3.3 MB)
  • 4. How to Succeed in this Course.vtt (3.5 KB)
2. K-Means Clustering
  • 1. An Easy Introduction to K-Means Clustering.mp4 (12.6 MB)
  • 1. An Easy Introduction to K-Means Clustering.vtt (8.3 KB)
  • 10. Using K-Means on Real Data MNIST.mp4 (10.7 MB)
  • 10. Using K-Means on Real Data MNIST.vtt (6.3 KB)
  • 11. One Way to Choose K.mp4 (9.1 MB)
  • 11. One Way to Choose K.vtt (4.5 KB)
  • 12. K-Means Application Finding Clusters of Related Words.mp4 (26.0 MB)
  • 12. K-Means Application Finding Clusters of Related Words.vtt (7.4 KB)
  • 2. Visual Walkthrough of the K-Means Clustering Algorithm.mp4 (4.9 MB)
  • 2. Visual Walkthrough of the K-Means Clustering Algorithm.vtt (3.3 KB)
  • 3. Soft K-Means.mp4 (25.3 MB)
  • 3. Soft K-Means.vtt (6.2 KB)
  • 4. The K-Means Objective Function.mp4 (3.0 MB)
  • 4. The K-Means Objective Function.vtt (1.9 KB)
  • 5. Soft K-Means in Python Code.mp4 (30.2 MB)
  • 5. Soft K-Means in Python Code.vtt (6.9 KB)
  • 6. Visualizing Each Step of K-Means.mp4 (5.3 MB)
  • 6. Visualizing Each Step of K-Means.vtt (2.4 KB)
  • 7. Examples of where K-Means can fail.mp4 (17.0 MB)
  • 7. Examples of where K-Means can fail.vtt (4.5 KB)
  • 8. Disadvantages of K-Means Clustering.mp4 (3.9 MB)
  • 8. Disadvantages of K-Means Clustering.vtt (3.0 KB)
  • 9. How to Evaluate a Clustering (Purity, Davies-Bouldin Index).mp4 (11.4 MB)
  • 9. How to Evaluate a Clustering (Purity, Davies-Bouldin Index).vtt (8.1 KB)
3. Hierarchical Clustering
  • 1. Visual Walkthrough of Agglomerative Hierarchical Clustering.mp4 (4.4 MB)
  • 1. Visual Walkthrough of Agglomerative Hierarchical Clustering.vtt (3.2 KB)
  • 2. Agglomerative Clustering Options.mp4 (6.2 MB)
  • 2. Agglomerative Clustering Options.vtt (4.9 KB)
  • 3. Using Hierarchical Clustering in Python and Interpreting the Dendrogram.mp4 (11.9 MB)
  • 3. Using Hierarchical Clustering in Python and Interpreting the Dendrogram.vtt (3.9 KB)
  • 4. Application Evolution.mp4 (26.4 MB)
  • 4. Application Evolution.vtt (14.3 KB)
  • 5. Application Donald Trump vs. Hillary Clinton Tweets.mp4 (35.3 MB)
  • 5. Application Donald Trump vs. Hillary Clinton Tweets.vtt (16.9 KB)
4. Gaussian Mixture Models (GMMs)
  • 1. Description of the Gaussian Mixture Model and How to Train a GMM.mp4 (5.2 MB)
  • 1. Description of the Gaussian Mixture Model and How to Train a GMM.vtt (3.3 KB)
  • 2. Comparison between GMM and K-Means.mp4 (3.0 MB)
  • 2. Comparison between GMM and K-Means.vtt (2.0 KB)
  • 3. Write a Gaussian Mixture Model in Python Code.mp4 (30.1 MB)
  • 3. Write a Gaussian Mixture Model in Python Code.vtt (6.9 KB)
  • 4. Practical Issues with GMM Singular Covariance.mp4 (5.0 MB)
  • 4. Practical Issues with GMM Singular Covariance.vtt (3.6 KB)
  • 5. Kernel Density Estimation.mp4 (3.7 MB)
  • 5. Kernel Density Estimation.vtt (2.9 KB)
  • 6. Expectation-Maximization.mp4 (3.5 MB)
  • 6. Expectation-Maximization.vtt (2.4 KB)
  • 7. Future Unsupervised Learning Algorithms You Will Learn.mp4 (2.0 MB)
  • 7. Future Unsupervised Learning Algorithms You Will Learn.vtt (1.3 KB)
5. Appendix
  • 1. What is the Appendix.mp4 (5.5 MB)
  • 1. What is the Appendix.vtt (3.3 KB)
  • 10. What order should I take your courses in (part 1).mp4 (29.3 MB)
  • 10. What order should I take your courses in (part 1).vtt (14.1 KB)
  • 11. What order should I take your courses in (part 2).mp4 (37.6 MB)
  • 11. What order should I take your courses in (part 2).vtt (20.2 KB)
  • 2. Windows-Focused Environment Setup 2018.mp4 (186.3 MB)
  • 2. Windows-Focused Environment Setup 2018.vtt (17.4 KB)
  • 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 (43.9 MB)
  • 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt (12.4 KB)
  • 4. How to Code by Yourself (part 1).mp4 (24.5 MB)
  • 4. How to Code by Yourself (part 1).vtt (19.8 KB)
  • 5. How to Code by Yourself (part 2).mp4 (14.8 MB)
  • 5. How to Code by Yourself (part 2).vtt (11.6 KB)
  • 6. How to Succeed in this Course (Long Version).mp4 (18.3 MB)
  • 6. How to Succeed in this Course (Long Version).vtt (12.8 KB)
  • 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 (39.0 MB)
  • 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt (27.8 KB)
  • 8. Proof that using Jupyter Notebook is the same as not using it.mp4 (78.3 MB)
  • 8. Proof that using Jupyter Notebook is the same as not using it.vtt (78.3 MB)
  • 9. Python 2 vs Python 3.mp4 (7.8 MB)
  • 9. Python 2 vs Python 3.vtt (5.4 KB)
  • [CourseClub.Me].url (0.0 KB)
  • [DesireCourse.Net].url (0.0 KB)

Description

Cluster Analysis and Unsupervised Machine Learning in Python

Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE.

For More Courses Visit: https://desirecourse.net



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Udemy - Cluster Analysis and Unsupervised Machine Learning in Python [Desire Course]

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Download torrent
881.5 MB
seeders:14
leechers:9
Udemy - Cluster Analysis and Unsupervised Machine Learning in Python [Desire Course]

Torrent hash: D6DEF40031F087EF0911ECF51D1247DB300B31AA