Machine Learning Bookcamp, Video Edition

Machine Learning Bookcamp, Video Edition2.8 GB
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  - 1 - Chapter 1 Introduction to machine learning.mp475.1 MB
  - 10 - Chapter 2 Validating the model.mp467.5 MB
  - 11 - Chapter 2 Regularization.mp438.6 MB
  - 12 - Chapter 2 Using the model.mp440.8 MB
  - 13 - Chapter 3 Machine learning for classification.mp462.7 MB
  - 14 - Chapter 3 Initial data preparation.mp451.1 MB
  - 15 - Chapter 3 Feature importance, Part 1.mp454.0 MB
  - 16 - Chapter 3 Feature importance, Part 2.mp440.5 MB
  - 17 - Chapter 3 Feature engineering.mp441.6 MB
  - 18 - Chapter 3 Machine learning for classification.mp431.2 MB
  - 19 - Chapter 3 Training logistic regression.mp450.9 MB
  - 2 - Chapter 1 When machine learning isn’t helpful.mp476.7 MB
  - 20 - Chapter 3 Model interpretation.mp463.6 MB
  - 21 - Chapter 3 Using the model.mp467.8 MB
  - 22 - Chapter 4 Evaluation metrics for classification.mp454.7 MB
  - 23 - Chapter 4 Confusion table.mp456.2 MB
  - 24 - Chapter 4 Precision and recall.mp430.1 MB
  - 25 - Chapter 4 ROC curve and AUC score.mp466.0 MB
  - 26 - Chapter 4 ROC Curve.mp457.5 MB
  - 27 - Chapter 4 Parameter tuning.mp435.0 MB
  - 28 - Chapter 4 Next steps.mp465.1 MB
  - 29 - Chapter 5 Deploying machine learning models.mp442.9 MB
  - 3 - Chapter 1 Evaluation.mp469.3 MB
  - 30 - Chapter 5 Model serving.mp450.3 MB
  - 31 - Chapter 5 Managing dependencies.mp439.9 MB
  - 32 - Chapter 5 Docker.mp434.8 MB
  - 33 - Chapter 5 Deployment.mp448.3 MB
  - 34 - Chapter 6 Decision trees and ensemble learning.mp430.4 MB
  - 35 - Chapter 6 Data cleaning.mp452.3 MB