https://github.com/adamrossnelson/maclearn
Repo for testing Machine Learning
https://github.com/adamrossnelson/maclearn
Last synced: 3 months ago
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Repo for testing Machine Learning
- Host: GitHub
- URL: https://github.com/adamrossnelson/maclearn
- Owner: adamrossnelson
- Created: 2018-03-16T21:41:39.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2020-04-16T22:11:37.000Z (about 5 years ago)
- Last Synced: 2025-01-10T04:54:24.075Z (4 months ago)
- Language: Jupyter Notebook
- Size: 2.29 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# MacLearn
Repo for testing or demonstrating Machine Learning
## Example using auto2.dta
The dataset `auto2.dta` is available from Stata. Files collected in subfolder [auto2dta](https://github.com/adamrossnelson/MacLearn/tree/master/auto2dta) use machine learning with the `auto2.dta`. The goal is to predict if a vehicle is either foriegn or domestic. This example uses a decision tree.
The files in subfolder [KerasTemplate](https://github.com/adamrossnelson/MacLearn/tree/master/KerasTemplate) illustrate machine learning with `sonar.csv`. The goal is to predict if a sonar signal is detecting either a metal cynlinder or a rock. This example uses a neural network, it is based on guidance at [Machine Learning Mastery](https://machinelearningmastery.com).
The files in subfoder [Whimsical](https://github.com/adamrossnelson/MacLearn/tree/master/whimsical) are tinkerings that follow from this [Anaconda tutorial](https://know.anaconda.com/rs/387-XNW-688/images/ML.html). Maybe you're a fan of replication science? This might be called replication tutorials.
# Example Datasets
* [19 Free Public Data Sets For Your First Data Science Project](https://www.springboard.com/blog/free-public-data-sets-data-science-project/)
* [Data.Gov](https://www.data.gov/)
* [Kaggle Datasets](https://www.kaggle.com/datasets)
# Other Resources
* [Binary Classification Tutorial with the Keras Deep Learning Library](https://machinelearningmastery.com/binary-classification-tutorial-with-the-keras-deep-learning-library/).
* [First Neural Network in Python With Keras Step-By-Step
](https://machinelearningmastery.com/tutorial-first-neural-network-python-keras/).
* [Make Predictions with Keras](https://machinelearningmastery.com/how-to-make-classification-and-regression-predictions-for-deep-learning-models-in-keras/).
* [Happiness Prediction Example](https://github.com/kudchikarsk/happiness-prediction/blob/master/LearnHappiness.ipynb).
* Siraj Raval's [Keras Explained](https://www.youtube.com/watch?v=j_pJmXJwMLA&t=43s).