| 文件 | 大小 |
|---|
| 1.Introduction/01.Leveraging machine learning.mp4 | 19.14 MB |
| 1.Introduction/02.What you should know.mp4 | 4.49 MB |
| 1.Introduction/03.What tools you need.mp4 | 1.62 MB |
| 1.Introduction/04.Using the exercise files.mp4 | 3.06 MB |
| 2.1. Machine Learning Basics/05.What is machine learning.mp4 | 5.98 MB |
| 2.1. Machine Learning Basics/06.What kind of problems can this help you solve.mp4 | 8.31 MB |
| 2.1. Machine Learning Basics/07.Why Python.mp4 | 12.14 MB |
| 2.1. Machine Learning Basics/08.Machine learning vs. Deep learning vs. Artificial intelligence.mp4 | 6.87 MB |
| 2.1. Machine Learning Basics/09.Demos of machine learning in real life.mp4 | 10.55 MB |
| 2.1. Machine Learning Basics/10.Common challenges.mp4 | 8.98 MB |
| 3.2. Exploratory Data Analysis and Data Cleaning/11.Why do we need to explore and clean our data.mp4 | 5.20 MB |
| 3.2. Exploratory Data Analysis and Data Cleaning/12.Exploring continuous features.mp4 | 24.23 MB |
| 3.2. Exploratory Data Analysis and Data Cleaning/13.Plotting continuous features.mp4 | 17.86 MB |
| 3.2. Exploratory Data Analysis and Data Cleaning/14.Continuous data cleaning.mp4 | 15.07 MB |
| 3.2. Exploratory Data Analysis and Data Cleaning/15.Exploring categorical features.mp4 | 15.14 MB |
| 3.2. Exploratory Data Analysis and Data Cleaning/16.Plotting categorical features.mp4 | 14.29 MB |
| 3.2. Exploratory Data Analysis and Data Cleaning/17.Categorical data cleaning.mp4 | 11.02 MB |
| 4.3. Measuring Success/18.Why do we split up our data.mp4 | 9.49 MB |
| 4.3. Measuring Success/19.Split data for train_validation_test set.mp4 | 12.99 MB |
| 4.3. Measuring Success/20.What is cross-validation.mp4 | 9.04 MB |
| 4.3. Measuring Success/21.Establish an evaluation framework.mp4 | 6.98 MB |
| 5.4. Optimizing a Model/22.Bias_Variance tradeoff.mp4 | 8.11 MB |
| 5.4. Optimizing a Model/23.What is underfitting.mp4 | 4.04 MB |
| 5.4. Optimizing a Model/24.What is overfitting.mp4 | 4.61 MB |
| 5.4. Optimizing a Model/25.Finding the optimal tradeoff.mp4 | 5.45 MB |
| 5.4. Optimizing a Model/26.Hyperparameter tuning.mp4 | 9.63 MB |
| 5.4. Optimizing a Model/27.Regularization.mp4 | 4.41 MB |
| 6.5. End-to-End Pipeline/28.Overview of the process.mp4 | 2.57 MB |
| 6.5. End-to-End Pipeline/29.Clean continuous features.mp4 | 13.79 MB |
| 6.5. End-to-End Pipeline/30.Clean categorical features.mp4 | 10.62 MB |
| 6.5. End-to-End Pipeline/31.Split data into train_validation_test set.mp4 | 9.71 MB |
| 6.5. End-to-End Pipeline/32.Fit a basic model using cross-validation.mp4 | 14.91 MB |
| 6.5. End-to-End Pipeline/33.Tune hyperparameters.mp4 | 18.15 MB |
| 6.5. End-to-End Pipeline/34.Evaluate results on validation set.mp4 | 18.55 MB |
| 6.5. End-to-End Pipeline/35.Final model selection and evaluation on test set.mp4 | 24.12 MB |
| 7.Conclusion/36.Next steps.mp4 | 6.19 MB |
| Discuss.FTUForum.com.html | 31.89 kB |
| Exercise Files/Ex_Files_Applied_Machine_Learning.zip | 3.41 MB |
| FreeCoursesOnline.Me.html | 108.30 kB |
| FTUForum.com.html | 100.44 kB |
| How you can help Team-FTU.txt | 235.00 B |
| NulledPremium.com.url | 163.00 B |
| Torrent Downloaded From GloDls.to.txt | 84.00 B |
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