Pluralsight Path. Building Machine Learning Solutions with scikit-learn (2019)


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File Size:   2.95 GB
Creat Time:   2024-06-13
Active Degree:   145
Last Active:   2024-11-23
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File List

  1. C2. Scaling scikit-learn Solutions (Janani Ravi, 2019)/exercise.7z 137.39 MB
  2. B1. Building Neural Networks with scikit-learn (Janani Ravi, 2019)/exercise.7z 93.99 MB
  3. C1. Preparing Data for Modeling with scikit-learn (Janani Ravi, 2019)/exercise.7z 46.41 MB
  4. A1. Building Your First scikit-learn Solution (Janani Ravi, 2019)/2. Exploring scikit-learn for Machine Learning/07. Exploring scikit-learn Libraries.mp4 36.70 MB
  5. A2. Building Classification Models with scikit-learn (Janani Ravi, 2019)/exercise.7z 29.65 MB
  6. C3. Model Evaluation and Selection Using scikit-learn (Chetan Prabhu, 2019)/5. Model Selection Techniques/1. Model Selection Techniques.mp4 27.19 MB
  7. B2. Reducing Dimensions in Data with scikit-learn (Janani Ravi, 2019)/exercise.7z 23.95 MB
  8. C3. Model Evaluation and Selection Using scikit-learn (Chetan Prabhu, 2019)/3. Evaluation Methods for Classification Models/7. Demo.mp4 20.64 MB
  9. C3. Model Evaluation and Selection Using scikit-learn (Chetan Prabhu, 2019)/2. What Is Model Evaluation and Selection/1. Model Evaluation and Selection.mp4 20.54 MB
  10. C1. Preparing Data for Modeling with scikit-learn (Janani Ravi, 2019)/6. Working with Specialized Datasets/3. Exploring Internal Datasets.mp4 19.12 MB
  11. A4. Building Clustering Models with scikit-learn (Janani Ravi, 2019)/2. Building a Simple Clustering Model in scikit-learn/09. Evaluating K-means Clustering.mp4 18.44 MB
  12. C1. Preparing Data for Modeling with scikit-learn (Janani Ravi, 2019)/7. Performing Kernel Approximations/5. Comparing Classifiers Trained Using Implicit and Explict Features.mp4 18.03 MB
  13. C2. Scaling scikit-learn Solutions (Janani Ravi, 2019)/3. Observing the Factors Affecting Prediction Latency/06. Demo - Observing the Influence of Model Complexity.mp4 17.77 MB