amueller/COMS4995-s19

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amueller/COMS4995-s19

amueller

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COMS W4995 Applied Machine Learning - Spring 19

Applied Machine Learning Spring 2019

Materials for the course COMS4995 will be posted here.

You can find more details on the course (and an overview of the materials) on the course website.

Slides are in the slides subfolder.

Everything in this repository is licensed CC-0, meaning you can do with it whatever you want.

word_cloud

A little word cloud generator in Python

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"

Jupyter Notebook

scipy_2015_sklearn_tutorial

Scikit-Learn tutorial material for Scipy 2015

scipy-2016-sklearn

Scikit-learn tutorial at SciPy2016

Jupyter Notebook

ml-workshop-1-of-4

Introduction to Machine learning with Python, 4h interactive workshop

scipy-2017-sklearn

Scipy 2017 scikit-learn tutorial by Alex Gramfort and Andreas Mueller

Jupyter Notebook

scipy-2018-sklearn

Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller

Jupyter Notebook

COMS4995-s20

COMS W4995 Applied Machine Learning - Spring 20

Jupyter Notebook

mglearn

mglearn helper package for "Introduction to Machine Learning with Python"

ml-training-intro

Materials for the "Introduction to Machine Learning" class

ml-training-advanced

Materials for the "Advanced Scikit-learn" class in the afternoon

Jupyter Notebook

ml-workshop-4-of-4

Advanced Machine Learning with Scikit-learn part II

COMS4995-s18

COMS W4995 Applied Machine Learning - Spring 18

Jupyter Notebook

kaggle_insults

Kaggle Submission for "Detecting Insults in Social Commentary"

ml-workshop-3-of-4

Advanced Machine Learning with Scikit-learn part I

gco_python

Python wrappers for GCO alpha-expansion and alpha-beta-swaps

ml-workshop-2-of-4

Intermediate Machine Learning with Scikit-learn, 4h interactive workshop

advanced_training

Advanced Scikit-learn training session

Jupyter Notebook

futurepast

Deprecation tools for Python

talks_odt

Slides and materials for most of my talks by year

Jupyter Notebook

applied_ml_spring_2017

Website and material for the FIXME course on Practical Machine Learning

Jupyter Notebook

odscon-2015

Slides and material for open data science

odscon-sf-2015

Material for ODSCON San Francisco 2015

Jupyter Notebook

aml

Applied Machine Learning with Python

Jupyter Notebook

quick-ml-intro

One hour interactive training for ML with scikit-learn

Jupyter Notebook

pydata-nyc-advanced-sklearn

Notebooks (and slides) for my PyData NYC 2014 tutorial on the more advanced features of scikit-learn.

sklearn_tutorial

Slides for quick intro to machine learning with sklearn

sklearn-one-day

One day workshop for machine learning with scikit-learn

segmentation

Superpixel based semantic segmentation

scikit-learn-interactive-tutorial

IPython notebooks and data an interactive scikit-learn tutorial.

pydata-strata-2015

Slides and notebooks for PyData Strata San Jose

patsylearn

Patsy Adaptors for Scikit-learn

advanced_git_nyu_2016

Advanced git and github course material

textonboost

Texton boost implementation in C++ by Philipp Kraehenbuehl

pydata-amsterdam-2016

Machine Learning with Scikit-Learn (material for pydata Amsterdam 2016)

Jupyter Notebook

ml_meetup_nyc_2016

Material for Machine Learning Meetup "Machine Learning with Scikit-learn"

Jupyter Notebook

odsc_east_2016

Jupyter Notebook

speed_reading

Speed reading app with running focus

slic-python

SLIC wrapper for Python - legacy, rather use scikit-image now!

ml-workshop-short

Two hour interactive machine learning workshop

mlss_2015

Material for open source machine learning practical

jupytercon2017

Material for Data analysis and machine learning in Jupyter

Jupyter Notebook

structured-prediction-workshop

Introduction to structured prediction with Python and pystruct

information-theoretic-mst

Information Theoretic Clustering using Minimum Spanning Trees

advanced-sklearn-boston-nlp-2016

Material and slides for Boston NLP meetup May 23rd 2016

Jupyter Notebook

nyu_ml_lectures

Materials for NYU Machine Learning Guest Lectures

amueller.github.io

ImageNet-parsing-Python

Python class to explore the ImageNet database

water_hackweek_2020_machine_learning

Water Hackweek Machine Learning workshop

Jupyter Notebook

strata-nyc-2016

Materials fort Strata NYC 2016 scikit-learn tutorial

Jupyter Notebook

damascene-python-and-matlab-bindings

Python and matlab bindings for the Damascene CUDA implementation of gPB

git_workshop

Material for git workshop

strata_singapore_2015

Materials for Strata Singapore "Machine learning In Python with scikit-learn" tutorial.

Jupyter Notebook

sklearn_workshop

Jupyter notebooks for interactive scikit-learn workshop

cv

Curriculum Vitae

datasets

Datasets of some standard computer vision / deep learning benchmarks

GPU-Quickshift-Python-Bindings

Python bindings for Brian Fultersons really quick shift

structured_prediction_talk

Slides for explaining structured prediction and PyStruct

oss-directions-webinar-2019

Open Source Directions webinar materials

Jupyter Notebook

intro_to_ml_cuny_2015

Introduction to machine learning for CUNY

columbia-website

My official columbia page

phd-thesis-segmentation

unearthing my thesis - this is a backup

figures

Some figures and drawings for talks

daimrf

Python interface for inference with LibDAI

notebooks

Random notebooks

vim-config

nsf-biosketch

stand-alone nsf biosketch

oss_workshop

Demo repository for oss workshop

dask-learn

CZI-sklearn

gah

Code I don't want to keep reimplementing all the time

dotfiles

Another try to manage my dotfiles

icra_2014_crf_nyu

ICRA 2014 paper on crfs for semantic segmenation on the nyu dataset