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datasets
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figures
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images
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solutions
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01.1 Introduction to Machine Learning.ipynb
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01.2 IPython Numpy and Matplotlib Refresher.ipynb
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01.3 Data Representation for Machine Learning.ipynb
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01.4 Training and Testing Data.ipynb
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02.1 Supervised Learning - Classification.ipynb
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02.2 Supervised Learning - Regression.ipynb
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02.3 Unsupervised Learning - Transformations and Dimensionality Reduction.ipynb
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02.4 Unsupervised Learning - Clustering.ipynb
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02.5 Review of Scikit-learn API.ipynb
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03.1 Case Study - Supervised Classification of Handwritten Digits.ipynb
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03.2 Methods - Unsupervised Preprocessing.ipynb
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03.3 Case Study - Face Recognition with Eigenfaces.ipynb
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03.4 Methods - Text Feature Extraction.ipynb
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03.5 Case Study - SMS Spam Detection.ipynb
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03.6 Case Study - Titanic Survival.ipynb
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04.1 Cross Validation.ipynb
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04.2 Model Complexity and GridSearchCV.ipynb
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04.3 Analyzing Model Capacity.ipynb
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04.4 Model Evaluation and Scoring Metrics.ipynb
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05.1 In Depth - Linear Models.ipynb
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05.2 In Depth - Support Vector Machines.ipynb
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05.3 In Depth - Trees and Forests.ipynb
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06.1 Pipelining Estimators.ipynb
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07.1 Case Study - Large Scale Text Classification.ipynb
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helpers.py
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