| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/1.Introduction/01.Leveraging machine learning.mp4 |
19.1 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/1.Introduction/02.What you should know.mp4 |
4.5 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/1.Introduction/03.What tools you need.mp4 |
1.6 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/1.Introduction/04.Using the exercise files.mp4 |
3.1 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/05.What is machine learning.mp4 |
6 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/06.What kind of problems can this help you solve.mp4 |
8.3 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/07.Why Python.mp4 |
12.1 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/08.Machine learning vs. Deep learning vs. Artificial intelligence.mp4 |
6.9 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/09.Demos of machine learning in real life.mp4 |
10.6 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/10.Common challenges.mp4 |
9 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/11.Why do we need to explore and clean our data.mp4 |
5.2 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/12.Exploring continuous features.mp4 |
24.2 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/13.Plotting continuous features.mp4 |
17.9 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/14.Continuous data cleaning.mp4 |
15.1 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/15.Exploring categorical features.mp4 |
15.1 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/16.Plotting categorical features.mp4 |
14.3 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/17.Categorical data cleaning.mp4 |
11 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/4.3. Measuring Success/18.Why do we split up our data.mp4 |
9.5 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/4.3. Measuring Success/19.Split data for train_validation_test set.mp4 |
13 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/4.3. Measuring Success/20.What is cross-validation.mp4 |
9 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/4.3. Measuring Success/21.Establish an evaluation framework.mp4 |
7 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/22.Bias_Variance tradeoff.mp4 |
8.1 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/23.What is underfitting.mp4 |
4 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/24.What is overfitting.mp4 |
4.6 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/25.Finding the optimal tradeoff.mp4 |
5.4 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/26.Hyperparameter tuning.mp4 |
9.6 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/27.Regularization.mp4 |
4.4 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/28.Overview of the process.mp4 |
2.6 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/29.Clean continuous features.mp4 |
13.8 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/30.Clean categorical features.mp4 |
10.6 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/31.Split data into train_validation_test set.mp4 |
9.7 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/32.Fit a basic model using cross-validation.mp4 |
14.9 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/33.Tune hyperparameters.mp4 |
18.1 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/34.Evaluate results on validation set.mp4 |
18.5 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/35.Final model selection and evaluation on test set.mp4 |
24.1 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/7.Conclusion/36.Next steps.mp4 |
6.2 MB |
| [Lynda] Applied Machine Learning - Foundations/[Lynda] Applied Machine Learning - Foundations/Exercise Files/Ex_Files_Applied_Machine_Learning.zip |
3.4 MB |
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