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Machine Learning and AI Foundations - Classification Modeling

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种子名称: Machine Learning and AI Foundations - Classification Modeling
文件类型: 视频
文件数目: 31个文件
文件大小: 249.75 MB
收录时间: 2018-12-24 09:00
已经下载: 3
资源热度: 132
最近下载: 2024-11-6 02:11

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Machine Learning and AI Foundations - Classification Modeling.torrent
  • 4.3. Algorithms on Parade/18.Logistic regression.mp424.63MB
  • 1.Introduction/01.Classification problems in machine learning.mp43.9MB
  • 1.Introduction/02.What you should know.mp43.64MB
  • 1.Introduction/03.Defining terms.mp44.95MB
  • 2.1. The Big Picture - Defining Your Classification Strategy/04.The importance of binary classification.mp43.21MB
  • 2.1. The Big Picture - Defining Your Classification Strategy/05.Binary vs. multinomial.mp48.94MB
  • 2.1. The Big Picture - Defining Your Classification Strategy/06.So-called “black box” techniques.mp46.66MB
  • 2.1. The Big Picture - Defining Your Classification Strategy/07.One task, many algorithms.mp48.53MB
  • 2.1. The Big Picture - Defining Your Classification Strategy/08.Statistics vs. machine learning.mp46.68MB
  • 2.1. The Big Picture - Defining Your Classification Strategy/09.Model assessment vs. business evaluation.mp44.87MB
  • 3.2. How Do I Choose a 'Winner'/10.Training and test partitions.mp45.46MB
  • 3.2. How Do I Choose a 'Winner'/11.Lift Charts.mp43.37MB
  • 3.2. How Do I Choose a 'Winner'/12.Gains tables.mp44.46MB
  • 3.2. How Do I Choose a 'Winner'/13.Confusion matrix.mp46.07MB
  • 4.3. Algorithms on Parade/14.Overview.mp43.56MB
  • 4.3. Algorithms on Parade/15.Discriminant with three categories.mp412.15MB
  • 4.3. Algorithms on Parade/16.Discriminant with two categories.mp48.81MB
  • 4.3. Algorithms on Parade/17.Stepwise discriminant.mp41.76MB
  • 4.3. Algorithms on Parade/19.Stepwise logistic regression.mp41.74MB
  • 4.3. Algorithms on Parade/20.Decision Trees.mp49.24MB
  • 4.3. Algorithms on Parade/21.KNN.mp48.88MB
  • 4.3. Algorithms on Parade/22.Linear SVM.mp413.31MB
  • 4.3. Algorithms on Parade/23.Neural nets.mp414.87MB
  • 4.3. Algorithms on Parade/24.Bayesian networks.mp417.7MB
  • 4.3. Algorithms on Parade/25.Ensembles.mp49.42MB
  • 5.4. Common Modeling Challenges/26.Imbalanced target categories.mp45.83MB
  • 5.4. Common Modeling Challenges/27.Interactions.mp48.24MB
  • 5.4. Common Modeling Challenges/28.Missing data.mp46.67MB
  • 5.4. Common Modeling Challenges/29.Bias-variance trade-off and overfitting.mp411.2MB
  • 5.4. Common Modeling Challenges/30.Data reduction.mp415.34MB
  • 6.Conclusion/31.Next steps.mp45.65MB