Machine Learning and AI Foundations - Classification Modeling番号下载_Machine Learning and AI Foundations - Classification Modeling番号下载_Machine Learning and AI Foundations - Classification Modeling下载

Machine Learning and AI Foundations - Classification Modeling

种子简介

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次
资源热度： 144
最近下载： 2024-12-28 12:33

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:c603ecb0f78ac9b38623bbfde6e1ba46fc06fac5&dn=Machine Learning and AI Foundations - Classification Modeling 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

Machine Learning and AI Foundations - Classification Modeling

种子包含的文件

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