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01-classification-binary.ipynb
01-classification-binary.ipynb
 
 
01-clustering-introduction.ipynb
01-clustering-introduction.ipynb
 
 
01-numpy-and-pandas.ipynb
01-numpy-and-pandas.ipynb
 
 
01-training-regression.ipynb
01-training-regression.ipynb
 
 
02-classification-metrics.ipynb
02-classification-metrics.ipynb
 
 
02-experimenting-Regression.ipynb
02-experimenting-Regression.ipynb
 
 
02-kmeans-and-hierachial.ipynb
02-kmeans-and-hierachial.ipynb
 
 
02-visualize-data (1).ipynb
02-visualize-data (1).ipynb
 
 
02-visualize-data.ipynb
02-visualize-data.ipynb
 
 
03-classification-multiclass.ipynb
03-classification-multiclass.ipynb
 
 
03-real-world-data.ipynb
03-real-world-data.ipynb
 
 
03-tuning-regression.ipynb
03-tuning-regression.ipynb
 
 
1-3-exercise-create-ml-model.ipynb
1-3-exercise-create-ml-model.ipynb
 
 
5-3-exercise-feature-normalization.ipynb
5-3-exercise-feature-normalization.ipynb
 
 
5-5-exercise-test-training-datasets.ipynb
5-5-exercise-test-training-datasets.ipynb
 
 
5-7-exercise-test-set-nuances.ipynb
5-7-exercise-test-set-nuances.ipynb
 
 
README.md
README.md
 
 
example-of-a-deep-neural-network.png
example-of-a-deep-neural-network.png
 
 
example-of-kmeans-clusters.jpeg
example-of-kmeans-clusters.jpeg
 
 

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Statistical-Analysis-and-Machine-Learning-notebooks

A collection of jupyter notebooks showcasing how to perform statistical analysis using pandas library and machine learning using scikit-learn libraries in Python.

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A collection of jupyter notebooks showcasing how to perform statistical analysis using pandas library and machine learning using scikit-learn libraries in Python.

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