Developing Classification and Regression Systems (Machine Learning with Python for Everyone Series), Part 3

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size8.4 GB
  • Uploaded Bytutsnode
  • Downloads56
  • Last checkedJan. 21st '22
  • Date uploadedJan. 20th '22
  • Seeders 26
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Description

Developing Classification and Regression Systems (Machine Learning with Python for Everyone Series), Part 3

Sneak Peek

The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing.

Dr. Mark Fenner, owner of Fenner Training and Consulting, LLC, has taught computing and mathematics to diverse adult audiences since 1999, and holds a PhD in computer science. His research has included design, implementation, and performance of machine learning and numerical algorithms; developing learning systems to detect user anomalies; and probabilistic modeling of protein function.

Released 1/2022

Files:

Developing Classification and Regression Systems, Part 3 [TutsNode.com] - Developing Classification and Regression Systems, Part 3
  • 11 - 2.3 Discriminant Analysis I.mp4 (513.0 MB)
  • 31 - 5.2 Tuning Hyperparameters.mp4 (510.8 MB)
  • 4 - 1.2 Decision Trees I.mp4 (500.1 MB)
  • 27 - 4.5 Interactions.mp4 (498.7 MB)
  • 12 - 2.4 Discriminant Analysis II.mp4 (486.8 MB)
  • 16 - 3.1 Penalized Regression I.mp4 (476.4 MB)
  • 5 - 1.3 Decision Trees II.mp4 (447.6 MB)
  • 28 - 4.6 Target Manipulations.mp4 (426.1 MB)
  • 3 - 1.1 Revisiting Classification.mp4 (399.8 MB)
  • 7 - 1.5 Support Vector Classifiers II.mp4 (398.3 MB)
  • 10 - 2.2 Logistic Regression II.mp4 (371.4 MB)
  • 32 - 5.3 Nested Cross-validation.mp4 (342.4 MB)
  • 24 - 4.2 Feature Scaling.mp4 (300.9 MB)
  • 26 - 4.4 Categorical Coding.mp4 (278.6 MB)
  • 9 - 2.1 Logistic Regression I.mp4 (257.3 MB)
  • 6 - 1.4 Support Vector Classifiers I.mp4 (240.0 MB)
  • 25 - 4.3 Discretization.mp4 (231.6 MB)
  • 19 - 3.4 Regression Trees.mp4 (219.7 MB)
  • 18 - 3.3 Piecewise Constant Regression.mp4 (212.2 MB)
  • 30 - 5.1 Models, Parameters, and Hyperparameters.mp4 (191.3 MB)
  • 33 - 5.4 Pipelines.mp4 (190.6 MB)
  • 21 - 3.6 Comparing Regressors.mp4 (182.6 MB)
  • 14 - 2.6 Comparing Classifiers.mp4 (169.2 MB)
  • 17 - 3.2 Penalized Regression II.mp4 (143.7 MB)
  • 34 - 5.5 Tuning Pipelines.mp4 (136.7 MB)
  • 1 - Developing Classification and Regression Systems (Machine Learning with Python for Everyone Series), Part 3 LiveLessons - Introduction.mp4 (110.0 MB)
  • 20 - 3.5 Bias and Variance of Regressors.mp4 (86.6 MB)
  • 23 - 4.1 Overview of Feature Engineering.mp4 (70.9 MB)
  • 13 - 2.5 Bias and Variance of Classifiers.mp4 (70.4 MB)
  • 35 - Developing Classification and Regression Systems (Machine Learning with Python for Everyone Series), Part 3 LiveLessons - Summary.mp4 (35.3 MB)
  • 15 - Topics.mp4 (17.5 MB)
  • 29 - Topics.mp4 (17.0 MB)
  • 22 - Topics.mp4 (16.5 MB)
  • 8 - Topics.mp4 (14.5 MB)
  • 2 - Topics.mp4 (14.2 MB)
  • TutsNode.com.txt (0.1 KB)
  • [TGx]Downloaded from torrentgalaxy.to .txt (0.6 KB)
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