amueller / COMS4995-s18
COMS W4995 Applied Machine Learning - Spring 18
☆158Updated 5 years ago
Alternatives and similar repositories for COMS4995-s18:
Users that are interested in COMS4995-s18 are comparing it to the libraries listed below
- Materials for the "Advanced Scikit-learn" class in the afternoon☆165Updated 6 years ago
- Basics of programming: algorithms, data structures, object oriented programming☆93Updated 6 years ago
- Website and material for the FIXME course on Practical Machine Learning☆90Updated 7 years ago
- Implementation of different machine learning techniques☆94Updated 6 years ago
- Machine learning with Python tutorial at MSU Data Science 2018☆110Updated 7 years ago
- Scipy 2017 scikit-learn tutorial by Alex Gramfort and Andreas Mueller☆285Updated 7 years ago
- Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller☆248Updated 6 years ago
- PyCon 2017 tutorial on time series analysis☆72Updated 7 years ago
- Code snippets for "Introduction to Deep Learning with TensorFlow" at PyData Ann Arbor Aug 2017☆81Updated 7 years ago
- General Assembly repo for Data Science 18☆36Updated 10 years ago
- Doing Bayesian statistics in Python!☆67Updated 7 years ago
- Materials for GWU DNSC 6279 and DNSC 6290.☆238Updated 10 months ago
- Machine learning with scikit-learn tutorial at PyData Chicago 2016☆129Updated 8 years ago
- Code material for a data science tutorial☆199Updated 7 years ago
- ☆135Updated 5 years ago
- Scikit-Learn Tutorial for PyData Seattle 2015☆137Updated 9 years ago
- Advanced Scikit-learn training session☆118Updated 8 years ago
- Materials for the "Introduction to Machine Learning" class☆228Updated 6 years ago
- A Little Book of Python for Multivariate Analysis☆87Updated 9 years ago
- Neural networks from scratch☆108Updated 4 years ago
- General Assembly's Data Science course in Washington, DC☆185Updated 2 years ago
- Exploring most useful libraries of Python. Each notebook covers basic and advanced functionalities of a python library.☆53Updated 7 years ago
- A collection of notebook to learn the Applied Predictive Modeling using Python.☆275Updated 8 years ago
- Public Repository for cs109a, 2017 edition☆326Updated last year
- Code for a workshop on statistical interference using computational methods in Python.☆224Updated 4 years ago
- This contains materials for the word embeddings workshop☆126Updated 7 years ago
- Tutorials on visualizing data using python packages like bokeh, plotly, seaborn and igraph☆266Updated 4 years ago
- General Assembly's Data Science course in Washington, DC☆233Updated 10 months ago
- COMS W4995 Applied Machine Learning - Spring 19☆301Updated 5 years ago
- Slides and materials for most of my talks by year☆92Updated last year