Fundamentals of Machine Learning Course at DSR

Local Environment

To have these notebooks running locally, you need to follow these steps:

Clone the repo: git clone https://github.com/dvgodoy/ML_Fundamentals.git
Inside the folder of the clone repo, create a conda environment: conda env create -f environment.yml -n fund
Activate the virtual environment: conda activate fund
Run Jupyter: jupyter notebook

Obs.: environment.yml is conda's equivalent of requirements.txt Obs.: you need to have GraphViz installed as well

Binder

You can use Binder to open the notebooks on an executable environment - just click on the badge:

After it starts, it will open a familiar Jupyter notebook interface! Just run all cells, wait for the interactive plots to load and you're good to go!

Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
.gitignore		.gitignore
1. Linear Regression.ipynb		1. Linear Regression.ipynb
10. GradientBoostedTrees.ipynb		10. GradientBoostedTrees.ipynb
11. Logistic Regression.ipynb		11. Logistic Regression.ipynb
12. Evaluation Metrics for Classification.ipynb		12. Evaluation Metrics for Classification.ipynb
13. Support Vector Machine (SVM).ipynb		13. Support Vector Machine (SVM).ipynb
14. Dimensionality.ipynb		14. Dimensionality.ipynb
15. Eigenvectors and Eigenvalues.ipynb		15. Eigenvectors and Eigenvalues.ipynb
16. Principal Component Analysis (PCA).ipynb		16. Principal Component Analysis (PCA).ipynb
17. K-Nearest Neighbors (KNN).ipynb		17. K-Nearest Neighbors (KNN).ipynb
18. Clustering - KMeans.ipynb		18. Clustering - KMeans.ipynb
19. Neural Networks - Activation Functions.ipynb		19. Neural Networks - Activation Functions.ipynb
2. Bias Variance Trade-Off.ipynb		2. Bias Variance Trade-Off.ipynb
3. Norms and Distances.ipynb		3. Norms and Distances.ipynb
4. Regularized Regression.ipynb		4. Regularized Regression.ipynb
5. Scaling and Outliers.ipynb		5. Scaling and Outliers.ipynb
6. Gradient Descent.ipynb		6. Gradient Descent.ipynb
7. Homogeneity Metrics.ipynb		7. Homogeneity Metrics.ipynb
8. Decision Trees.ipynb		8. Decision Trees.ipynb
9. RandomForests.ipynb		9. RandomForests.ipynb
LICENSE		LICENSE
README.md		README.md
bias-variance2.png		bias-variance2.png
bias_variance.png		bias_variance.png
bias_vs_variance_error.png		bias_vs_variance_error.png
confusion_matrix.png		confusion_matrix.png
custom.css		custom.css
environment.yml		environment.yml
train-validate-test.png		train-validate-test.png

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Fundamentals of Machine Learning Course at DSR

Local Environment

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