https://github.com/amueller/advanced_training

Advanced Scikit-learn training session

https://github.com/amueller/advanced_training

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

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  • codemeta.json file
    Found codemeta.json file
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  • Academic publication links
  • Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
  • Institutional organization owner
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  • Scientific vocabulary similarity
    Low similarity (6.2%) to scientific vocabulary
Last synced: 11 months ago · JSON representation

Repository

Advanced Scikit-learn training session

Basic Info
  • Host: GitHub
  • Owner: amueller
  • License: bsd-2-clause
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 41.2 MB
Statistics
  • Stars: 118
  • Watchers: 8
  • Forks: 40
  • Open Issues: 1
  • Releases: 0
Created about 10 years ago · Last pushed about 10 years ago
Metadata Files
Readme License

README.md

advanced_training

Advanced Scikit-learn training session

Outline

1 Basic algorithms

  • Review of supervised learning
  • Linear models for classification and regression
  • Loss functions, regularization, empirical risk minimization
  • Path algorithms
  • Exercise: FIXME Regression

2 Basic tools

  • Cross-validation vs train/test split
  • GridSearchCV
  • Overfitting Parameters
  • Scoring Metrics
  • Exercise: FIXME

3 Preprocessing

  • Scaling and normalization
  • Feature selection:
    • Univariate
    • Model-based
    • RFE
    • Forward / backward selection
  • Polynomial and interaction features

  • Exercise: FIXME

4 Advanced tools

  • Pipelines
  • FeatureUnion
  • Function Transformer?
  • Exercise: FIXME

5 Advanced Supervised Learning

  • Decision Tree Recap
  • Random Forests
  • Gradient Boosting / xgboost
  • Kernel SVMs
  • Kernel approximation
  • Neural Networks
  • Exercise: FIXME

6 Unsupervised feature extraction and visualization

  • PCA
  • NMF
  • Robust PCA?
  • TSNE
  • Exercise: FIXME

7 Outlier Detection

  • Elliptic Envelope?
  • IForest ?
  • What else?
  • KDE?
  • SVM?
  • robust PCA?
  • Exercise: FIXME

8 Gaussian Processes

  • Non-iid data
  • Gaussian fit...
  • Covariance matrix is a kernel
  • regression, outlier detection, time series modelling
  • Exercise: FIXME

9 More Neural Networks

10 beyond standard sklearn

  • warm starts
  • out of core
  • custom estimators

Owner

  • Name: Andreas Mueller
  • Login: amueller
  • Kind: user
  • Location: Los Gatos
  • Company: Microsoft

Scikit-learn core-developer, Principal Research SDE @microsoft

GitHub Events

Total
Last Year

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 45
  • Total Committers: 2
  • Avg Commits per committer: 22.5
  • Development Distribution Score (DDS): 0.022
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Andreas Mueller a****r@n****u 44
Andreas Mueller t****t@g****m 1
Committer Domains (Top 20 + Academic)
nyu.edu: 1

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 1
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 1
  • Total pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • alonsopg (1)
Pull Request Authors
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