https://github.com/districtdatalabs/navyfcu-ml

Notebooks and data for Machine Learning course.
https://github.com/districtdatalabs/navyfcu-ml

Last synced: 11 months ago
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Notebooks and data for Machine Learning course.

• Host: GitHub
• URL: https://github.com/districtdatalabs/navyfcu-ml
• Owner: DistrictDataLabs
• License: mit
• Created: 2018-09-07T13:40:33.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2018-10-07T17:09:14.000Z (over 7 years ago)
• Last Synced: 2025-01-09T08:27:47.180Z (about 1 year ago)
• Language: HTML
• Size: 15.5 MB
• Stars: 4
• Watchers: 3
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Generalized Machine Learning

This repository contains notebooks, data, and slides for the survey of generalized machine learning and distributed computing training from September 14, 2018 - September 28, 2018. During this three day course, we will cover the following topics:

Day One:

- ML Review: Generalized ML and Spatial Learning, Bias/Variance Tradeoff, Model Selection Triple

- Regularized Regression: LASSO vs Ridge; ElasticNet and more

- Clustering: Partitive vs Agglomerative Clustering; clustering evaluation methods, visualization

- Classification I: Instance and Inductive Models (kNN, Decision Trees, Ensembles of Trees)

Day 2:

- Classification II: Parametric Models: SVMs, Bayesian Models, Logistic Regression

- Dimensionality Reduction and Manifolds: PCA, SVD, tSNE, Isomaps

- Neural Networks I: Multi-Layer Perceptrons

- Neural Networks II: Deep Learning and Tensorflow

Day 3:

- Introduction to Spark: RDDs and Architecture  

- Programming Spark - interactive analysis and distributed jobs

- Using Spark for data analysis: Spark SQL and Spark DataFrames

- Spark for distributed ML: Spark MLlib