DataLearn Supervised ML Intro 2019

The repository of the hands-on introduction to machine learning workshop of the DataLearn 2019 track at DataHack 2019.

Notebooks by Shay Palachy. Presentation by Shay Palachy and Dana Kaner. (Thank you Dana <3)

Resources

Tools of the trade
- Jupyter notebooks
- numpy
- pandas
Data exploration
Preprocessing
- Imputation
- Scaling and normalization
- Handling outliers
- Feature extraction/generation
- Feature selection
- Dimensionality reduction
Modeling
- Model fit & loss functions
- Splitting your data
- Model evaluation
- Hyperparameter Optimization

Name		Name	Last commit message	Last commit date
Latest commit History 43 Commits
data		data
datalearn19intro		datalearn19intro
.gitignore		.gitignore
Intro to Machine Learning.pdf		Intro to Machine Learning.pdf
README.rst		README.rst
part_1.introducing_jupyter.ipynb		part_1.introducing_jupyter.ipynb
part_2.numpy.ipynb		part_2.numpy.ipynb
part_3.pandas.ipynb		part_3.pandas.ipynb
part_4.EDA.ipynb		part_4.EDA.ipynb
part_5.Preprocessing.ipynb		part_5.Preprocessing.ipynb
part_6.modeling.ipynb		part_6.modeling.ipynb
util_0.reading_the_data.ipynb		util_0.reading_the_data.ipynb