There are no reviews yet. Be the first to send feedback to the community and the maintainers!
word_cloud
A little word cloud generator in Pythonintroduction_to_ml_with_python
Notebooks and code for the book "Introduction to Machine Learning with Python"scipy_2015_sklearn_tutorial
Scikit-Learn tutorial material for Scipy 2015scipy-2016-sklearn
Scikit-learn tutorial at SciPy2016ml-workshop-1-of-4
Introduction to Machine learning with Python, 4h interactive workshopCOMS4995-s19
COMS W4995 Applied Machine Learning - Spring 19scipy-2017-sklearn
Scipy 2017 scikit-learn tutorial by Alex Gramfort and Andreas Muellerscipy-2018-sklearn
Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas MuellerCOMS4995-s20
COMS W4995 Applied Machine Learning - Spring 20mglearn
mglearn helper package for "Introduction to Machine Learning with Python"ml-training-intro
Materials for the "Introduction to Machine Learning" classml-training-advanced
Materials for the "Advanced Scikit-learn" class in the afternoonml-workshop-4-of-4
Advanced Machine Learning with Scikit-learn part IICOMS4995-s18
COMS W4995 Applied Machine Learning - Spring 18kaggle_insults
Kaggle Submission for "Detecting Insults in Social Commentary"ml-workshop-3-of-4
Advanced Machine Learning with Scikit-learn part Igco_python
Python wrappers for GCO alpha-expansion and alpha-beta-swapsml-workshop-2-of-4
Intermediate Machine Learning with Scikit-learn, 4h interactive workshopadvanced_training
Advanced Scikit-learn training sessionfuturepast
Deprecation tools for Pythontalks_odt
Slides and materials for most of my talks by yearapplied_ml_spring_2017
Website and material for the FIXME course on Practical Machine Learningodscon-2015
Slides and material for open data scienceodscon-sf-2015
Material for ODSCON San Francisco 2015aml
Applied Machine Learning with Pythonquick-ml-intro
One hour interactive training for ML with scikit-learnpydata-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 sklearnsklearn-one-day
One day workshop for machine learning with scikit-learnsegmentation
Superpixel based semantic segmentationscikit-learn-interactive-tutorial
IPython notebooks and data an interactive scikit-learn tutorial.pydata-strata-2015
Slides and notebooks for PyData Strata San Josepatsylearn
Patsy Adaptors for Scikit-learnadvanced_git_nyu_2016
Advanced git and github course materialpydata-amsterdam-2016
Machine Learning with Scikit-Learn (material for pydata Amsterdam 2016)ml_meetup_nyc_2016
Material for Machine Learning Meetup "Machine Learning with Scikit-learn"odsc_east_2016
speed_reading
Speed reading app with running focusslic-python
SLIC wrapper for Python - legacy, rather use scikit-image now!ml-workshop-short
Two hour interactive machine learning workshopmlss_2015
Material for open source machine learning practicaljupytercon2017
Material for Data analysis and machine learning in Jupyterstructured-prediction-workshop
Introduction to structured prediction with Python and pystructinformation-theoretic-mst
Information Theoretic Clustering using Minimum Spanning Treesadvanced-sklearn-boston-nlp-2016
Material and slides for Boston NLP meetup May 23rd 2016nyu_ml_lectures
Materials for NYU Machine Learning Guest Lecturesamueller.github.io
ImageNet-parsing-Python
Python class to explore the ImageNet databasewater_hackweek_2020_machine_learning
Water Hackweek Machine Learning workshopstrata-nyc-2016
Materials fort Strata NYC 2016 scikit-learn tutorialdamascene-python-and-matlab-bindings
Python and matlab bindings for the Damascene CUDA implementation of gPBgit_workshop
Material for git workshopstrata_singapore_2015
Materials for Strata Singapore "Machine learning In Python with scikit-learn" tutorial.sklearn_workshop
Jupyter notebooks for interactive scikit-learn workshopcv
Curriculum Vitaedatasets
Datasets of some standard computer vision / deep learning benchmarksGPU-Quickshift-Python-Bindings
Python bindings for Brian Fultersons really quick shiftstructured_prediction_talk
Slides for explaining structured prediction and PyStructoss-directions-webinar-2019
Open Source Directions webinar materialsintro_to_ml_cuny_2015
Introduction to machine learning for CUNYcolumbia-website
My official columbia pagephd-thesis-segmentation
unearthing my thesis - this is a backupfigures
Some figures and drawings for talksdaimrf
Python interface for inference with LibDAInotebooks
Random notebooksvim-config
nsf-biosketch
stand-alone nsf biosketchoss_workshop
Demo repository for oss workshopdask-learn
CZI-sklearn
gah
Code I don't want to keep reimplementing all the timedotfiles
Another try to manage my dotfilesicra_2014_crf_nyu
ICRA 2014 paper on crfs for semantic segmenation on the nyu datasetLove Open Source and this site? Check out how you can help us