ML-Mastery-with-python

This repository includes code samples from the book "Machine learning mastery with Python" by Dr. Jason Brownlee.

Thanks and regards,
Arvind

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ML-Mastery-with-python

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Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
Boston.csv		Boston.csv
Chapter 10 ML Algorithm performance metrics.ipynb		Chapter 10 ML Algorithm performance metrics.ipynb
Chapter 11 Spot check classification algorithms.ipynb		Chapter 11 Spot check classification algorithms.ipynb
Chapter 12 Spot check regression algorithms.ipynb		Chapter 12 Spot check regression algorithms.ipynb
Chapter 13 compare machine learning algorithms.ipynb		Chapter 13 compare machine learning algorithms.ipynb
Chapter 14 Automate machine learning pipelines.ipynb		Chapter 14 Automate machine learning pipelines.ipynb
Chapter 15 Improve performance with ensembles .ipynb		Chapter 15 Improve performance with ensembles .ipynb
Chapter 16 Improve performance with algorithm tuning.ipynb		Chapter 16 Improve performance with algorithm tuning.ipynb
Chapter 17 Save and Load ML models.ipynb		Chapter 17 Save and Load ML models.ipynb
Chapter 19 First ML project.ipynb		Chapter 19 First ML project.ipynb
Chapter 20 Regression machine learning case study project.ipynb		Chapter 20 Regression machine learning case study project.ipynb
Chapter 21 Binary classification ML project.ipynb		Chapter 21 Binary classification ML project.ipynb
Chapter 3 crash course in python and SciPy.ipynb		Chapter 3 crash course in python and SciPy.ipynb
Chapter 4 How to load machine learning data.ipynb		Chapter 4 How to load machine learning data.ipynb
Chapter 5 Understand your data with descriptive statistics.ipynb		Chapter 5 Understand your data with descriptive statistics.ipynb
Chapter 6 Understand your data with visualisation.ipynb		Chapter 6 Understand your data with visualisation.ipynb
Chapter 7 Prepare your data for machine learning.ipynb		Chapter 7 Prepare your data for machine learning.ipynb
Chapter 8 Feature selection for machine learning.ipynb		Chapter 8 Feature selection for machine learning.ipynb
Chapter 9 Evaluate the performance of ML algorithms with resampling .ipynb		Chapter 9 Evaluate the performance of ML algorithms with resampling .ipynb
README.md		README.md
finaized_model.sav		finaized_model.sav
finalized_model.sav		finalized_model.sav
housing.csv		housing.csv
iris.data.csv		iris.data.csv
pima-indians-diabetes.data.csv		pima-indians-diabetes.data.csv
sonar.all-data.csv		sonar.all-data.csv

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