[FreeCoursesOnline.Me] [LYNDA] Applied Machine Learning Foundations [FCO]

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文档个数：43个文档
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收录时间：2021-03-14
最近下载：2025-05-15
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3.2. Exploratory Data Analysis and Data Cleaning/12.Exploring continuous features.mp4 25.4 MB
6.5. End-to-End Pipeline/35.Final model selection and evaluation on test set.mp4 25.3 MB
1.Introduction/01.Leveraging machine learning.mp4 20.1 MB
6.5. End-to-End Pipeline/34.Evaluate results on validation set.mp4 19.4 MB
6.5. End-to-End Pipeline/33.Tune hyperparameters.mp4 19.0 MB
3.2. Exploratory Data Analysis and Data Cleaning/13.Plotting continuous features.mp4 18.7 MB
3.2. Exploratory Data Analysis and Data Cleaning/15.Exploring categorical features.mp4 15.9 MB
3.2. Exploratory Data Analysis and Data Cleaning/14.Continuous data cleaning.mp4 15.8 MB
6.5. End-to-End Pipeline/32.Fit a basic model using cross-validation.mp4 15.6 MB
3.2. Exploratory Data Analysis and Data Cleaning/16.Plotting categorical features.mp4 15.0 MB
6.5. End-to-End Pipeline/29.Clean continuous features.mp4 14.5 MB
4.3. Measuring Success/19.Split data for train_validation_test set.mp4 13.6 MB
2.1. Machine Learning Basics/07.Why Python.mp4 12.7 MB
3.2. Exploratory Data Analysis and Data Cleaning/17.Categorical data cleaning.mp4 11.6 MB
6.5. End-to-End Pipeline/30.Clean categorical features.mp4 11.1 MB
2.1. Machine Learning Basics/09.Demos of machine learning in real life.mp4 11.1 MB
6.5. End-to-End Pipeline/31.Split data into train_validation_test set.mp4 10.2 MB
5.4. Optimizing a Model/26.Hyperparameter tuning.mp4 10.1 MB
4.3. Measuring Success/18.Why do we split up our data.mp4 9.9 MB
4.3. Measuring Success/20.What is cross-validation.mp4 9.5 MB
2.1. Machine Learning Basics/10.Common challenges.mp4 9.4 MB
2.1. Machine Learning Basics/06.What kind of problems can this help you solve.mp4 8.7 MB
5.4. Optimizing a Model/22.Bias_Variance tradeoff.mp4 8.5 MB
4.3. Measuring Success/21.Establish an evaluation framework.mp4 7.3 MB
2.1. Machine Learning Basics/08.Machine learning vs. Deep learning vs. Artificial intelligence.mp4 7.2 MB
7.Conclusion/36.Next steps.mp4 6.5 MB
2.1. Machine Learning Basics/05.What is machine learning.mp4 6.3 MB
5.4. Optimizing a Model/25.Finding the optimal tradeoff.mp4 5.7 MB
3.2. Exploratory Data Analysis and Data Cleaning/11.Why do we need to explore and clean our data.mp4 5.4 MB
5.4. Optimizing a Model/24.What is overfitting.mp4 4.8 MB
1.Introduction/02.What you should know.mp4 4.7 MB
5.4. Optimizing a Model/27.Regularization.mp4 4.6 MB
5.4. Optimizing a Model/23.What is underfitting.mp4 4.2 MB
Exercise Files/Ex_Files_Applied_Machine_Learning.zip 3.6 MB
1.Introduction/04.Using the exercise files.mp4 3.2 MB
6.5. End-to-End Pipeline/28.Overview of the process.mp4 2.7 MB
1.Introduction/03.What tools you need.mp4 1.7 MB
FreeCoursesOnline.Me.html 110.9 kB
FTUForum.com.html 102.8 kB
Discuss.FTUForum.com.html 32.7 kB
How you can help Team-FTU.txt 235 Bytes
NulledPremium.com.url 163 Bytes
Torrent Downloaded From GloDls.to.txt 84 Bytes

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