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gmendozah / repository
This repo helps keep track about exercises, jupyter notebooks and datasets on the introduction to machine learning (pytorch) udacity nanodegree program.
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IMLND is a repo in which keeps track of the progress of the introduction to mahcine learning using pytorch offred by Udacity.
1. Introduction to Machine Learning
This section discusses the topic of What is Machine Learning?
Linear Regression.
Perceptron Algorithm.
Decision Trees.
Naive Bayes.
Support Vector Machines.
Ensemble Methods.
Model Evaluation Metrics.
Training and Tuning.
Introduction to Neural Networks.
Implementing Gradient Descent.
Training Neural Networks.
Deep Learning with PyTorch.
Clustering.
Hierarchical and Density Based Clustering.
Gaussian Mixture Models and Cluster Validation.
Dimensionality Reduction and PCA.
Random Projection and ICA.
This project requires Python 3.6.0 and the following Python libraries installed:
In a terminal or command window, navigate to the top-level project directory intro-to-machine-learning-with-pytorch/ (that contains this README) and run the following command:
jupyter notebook <your_archive>.ipynb
on any Jupyter Notebook. This will open the iPython Notebook software and project file in your browser.
Each project will be committed in the projects/ folder.
Verify here
This project uses the MIT License.