Udemy - Advanced Machine Learning Methods and Techniques (3.2025)

磁力链接/BT种子名称

Udemy - Advanced Machine Learning Methods and Techniques (3.2025)

磁力链接/BT种子简介

种子哈希：120d4ebc4f0240e41f8385a665d47d9887214c42
文件大小： 4.86G
已经下载：130次
下载速度：极快
收录时间：2025-07-27
最近下载：2025-09-28

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磁力链接下载

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文件列表

  • 3 - Advanced Models for Classification and Supervised Learning/7 -eXtreme Gradient Boosting Classifier (XGBoost).mp4 603.4 MB
  • 3 - Advanced Models for Classification and Supervised Learning/4 -Decision Tree Classifier.mp4 575.4 MB
  • 2 - Advanced Models for Regression and Supervised Learning/4 -Decision Tree Regression model.mp4 499.2 MB
  • 2 - Advanced Models for Regression and Supervised Learning/7 -eXtreme Gradient Boosting Regression (XGBoost).mp4 465.6 MB
  • 2 - Advanced Models for Regression and Supervised Learning/5 -Random Forest Regression.mp4 430.5 MB
  • 1 - Introduction/4 -The Conda Package Management System (optional).mp4 354.4 MB
  • 3 - Advanced Models for Classification and Supervised Learning/5 -Random Forest Classifier.mp4 347.5 MB
  • 3 - Advanced Models for Classification and Supervised Learning/6 -Voting Classifier.mp4 279.5 MB
  • 2 - Advanced Models for Regression and Supervised Learning/6 -Voting Regression.mp4 256.8 MB
  • 2 - Advanced Models for Regression and Supervised Learning/2 -Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron.mp4 243.9 MB
  • 2 - Advanced Models for Regression and Supervised Learning/3 -Feedforward Multi-Layer Perceptrons for Prediction.mp4 243.3 MB
  • 3 - Advanced Models for Classification and Supervised Learning/2 -Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron.mp4 227.5 MB
  • 1 - Introduction/1 -Introduction.mp4 182.2 MB
  • 3 - Advanced Models for Classification and Supervised Learning/3 -Feedforward Multi-Layer Perceptrons for Classification.mp4 180.1 MB
  • 1 - Introduction/3 -Download and installation of the Anaconda Distribution (optional).mp4 139.5 MB
  • 1 - Introduction/2 -Setup of the Anaconda Cloud Notebook.mp4 135.5 MB
  • 3 - Advanced Models for Classification and Supervised Learning/1 -Overview.mp4 29.1 MB
  • 2 - Advanced Models for Regression and Supervised Learning/1 -Overview.mp4 26.6 MB
  • 2 - Advanced Models for Regression and Supervised Learning/5 -Random Forest Regression.vtt 66.4 kB
  • 3 - Advanced Models for Classification and Supervised Learning/7 -eXtreme Gradient Boosting Classifier (XGBoost).vtt 65.3 kB
  • 2 - Advanced Models for Regression and Supervised Learning/3 -insurance.csv 61.3 kB
  • 2 - Advanced Models for Regression and Supervised Learning/4 -insurance.csv 61.3 kB
  • 2 - Advanced Models for Regression and Supervised Learning/5 -insurance.csv 61.3 kB
  • 2 - Advanced Models for Regression and Supervised Learning/6 -insurance.csv 61.3 kB
  • 2 - Advanced Models for Regression and Supervised Learning/7 -insurance.csv 61.3 kB
  • 3 - Advanced Models for Classification and Supervised Learning/4 -insurance.csv 61.3 kB
  • 3 - Advanced Models for Classification and Supervised Learning/4 -Decision Tree Classifier.vtt 59.0 kB
  • 2 - Advanced Models for Regression and Supervised Learning/7 -eXtreme Gradient Boosting Regression (XGBoost).vtt 51.5 kB
  • 2 - Advanced Models for Regression and Supervised Learning/4 -Decision Tree Regression model.vtt 48.1 kB
  • 3 - Advanced Models for Classification and Supervised Learning/7 -XGBoost_Classifier.py 46.2 kB
  • 2 - Advanced Models for Regression and Supervised Learning/6 -Voting Regression.vtt 44.1 kB
  • 3 - Advanced Models for Classification and Supervised Learning/6 -Voting Classifier.vtt 36.6 kB
  • 3 - Advanced Models for Classification and Supervised Learning/5 -Random Forest Classifier.vtt 34.8 kB
  • 1 - Introduction/4 -The Conda Package Management System (optional).vtt 31.7 kB
  • 2 - Advanced Models for Regression and Supervised Learning/3 -Feedforward Multi-Layer Perceptrons for Prediction.vtt 28.0 kB
  • 2 - Advanced Models for Regression and Supervised Learning/2 -Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron.vtt 22.1 kB
  • 3 - Advanced Models for Classification and Supervised Learning/2 -Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron.vtt 21.0 kB
  • 3 - Advanced Models for Classification and Supervised Learning/3 -Feedforward Multi-Layer Perceptrons for Classification.vtt 20.0 kB
  • 1 - Introduction/1 -Introduction.vtt 20.0 kB
  • 1 - Introduction/3 -Download and installation of the Anaconda Distribution (optional).vtt 17.1 kB
  • 2 - Advanced Models for Regression and Supervised Learning/7 -XGBoost_Regression.py 16.1 kB
  • 3 - Advanced Models for Classification and Supervised Learning/6 -Voting Classifier.py 15.8 kB
  • 2 - Advanced Models for Regression and Supervised Learning/5 -Random_Forest_regression.py 15.1 kB
  • 1 - Introduction/2 -Setup of the Anaconda Cloud Notebook.vtt 13.2 kB
  • 3 - Advanced Models for Classification and Supervised Learning/7 -wine.csv 13.0 kB
  • 3 - Advanced Models for Classification and Supervised Learning/4 -Decision_Tree_Classifier.py 9.7 kB
  • 2 - Advanced Models for Regression and Supervised Learning/6 -Voting_Regression_Ensemble.py 8.3 kB
  • 2 - Advanced Models for Regression and Supervised Learning/3 -MLP_Prediction.py 7.9 kB
  • 3 - Advanced Models for Classification and Supervised Learning/5 -Random_Forest_Classifier.py 6.8 kB
  • 2 - Advanced Models for Regression and Supervised Learning/4 -DecisionTree_regression.py 6.0 kB
  • 3 - Advanced Models for Classification and Supervised Learning/1 -Overview.vtt 3.4 kB
  • 3 - Advanced Models for Classification and Supervised Learning/3 -iris.csv 3.4 kB
  • 3 - Advanced Models for Classification and Supervised Learning/5 -iris.csv 3.4 kB
  • 3 - Advanced Models for Classification and Supervised Learning/6 -iris.csv 3.4 kB
  • 2 - Advanced Models for Regression and Supervised Learning/1 -Overview.vtt 3.3 kB
  • 3 - Advanced Models for Classification and Supervised Learning/3 -MLP_Classifier.py 3.2 kB

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本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！