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README.md

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@@ -23,7 +23,7 @@ Lecture 1
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Lecture 2
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| title | studio lab |
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| :---: | ---: |
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| Tree-based Models | Tree Models [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github//aws-samples/aws-machine-learning-university-accelerated-nlp/blob/master/notebooks/MLA-NLP-Lecture2-Tree-Models.ipynb)|
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| Tree-based Models | [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github//aws-samples/aws-machine-learning-university-accelerated-nlp/blob/master/notebooks/MLA-NLP-Lecture2-Tree-Models.ipynb)|
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| Regression Models |Linear Regression [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/aws-samples/aws-machine-learning-university-accelerated-nlp/blob/master/notebooks/MLA-NLP-Lecture2-Linear-Regression.ipynb) <br> Logistic Regression [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/aws-samples/aws-machine-learning-university-accelerated-nlp/blob/master/notebooks/MLA-NLP-Lecture2-Logistic-Regression.ipynb) |
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| Optimization-Regularization | - |
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| Hyperparameter Tuning | - |

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