PyDataSanLuis / conference
Slides and material from PyData San Luis 2017 conference
☆13Updated 7 years ago
Alternatives and similar repositories for conference:
Users that are interested in conference are comparing it to the libraries listed below
- Collection of code snippets and utilities for streamlit apps☆22Updated 4 years ago
- Source Code for 'Ontologies with Python' by Lamy Jean-Baptiste☆30Updated 3 years ago
- Know your ML Score based on Sculley's paper☆34Updated 5 years ago
- Teaching material and other info associated with the Information Extraction using Topic Models tutorial at SciPy US 2018.☆19Updated 6 years ago
- Public repository for versioning machine learning data☆42Updated 3 years ago
- The documentation for the Clustergrammer project☆10Updated 4 years ago
- Docker template for basic data science packages to interface with Neo4j☆14Updated 3 years ago
- Material for my PyData Jupyter & Pandas Workshops, I'm also available for personal in-house trainings on request☆65Updated 2 years ago
- Model drift detection☆11Updated last year
- Notebooks configured to be run with Binder, usually found on my blog.☆42Updated last year
- Bayesian statistics seminars☆30Updated 7 years ago
- Introduction to web scraping and text mining☆47Updated 4 years ago
- The goal of this repository is to detect the outliers for a dataset & see the impact of these outliers on predictive models☆23Updated 6 years ago
- Tutorial covering a new workflow available going from pandas to scikit-learn☆40Updated 2 years ago
- An in depth tutorial on sklearn's Pipeline and FeatureUnion classes.☆16Updated 7 years ago
- Building Python Data Application Tutorials☆23Updated 5 months ago
- ☆14Updated 2 years ago
- Project template for highly effective data science workflows☆29Updated 10 months ago
- Instant search for and access to many datasets in Pyspark.☆34Updated 2 years ago
- ☆16Updated 5 years ago
- Companion Notebooks and Data for Data Science with Python and Dask from Manning Publications☆51Updated 4 years ago
- Get introduced to Directed Acyclic Graphs (DAGs) through Dagster with a simple ML program☆12Updated last year
- How to use Python to understand data and transform the data into a tidy format ready to be used for modelling and visualisation.☆37Updated 5 years ago
- ☆15Updated 4 years ago
- ☆13Updated 9 years ago
- Visualization ideas for data science☆19Updated 6 years ago
- Building an API with the FastAPI framework to serve a scikit-learn model.☆18Updated 6 years ago
- Tutorial code and data for the entity resolution workshops.☆44Updated 9 years ago
- Code for my presentation: Using PySpark to Process Boat Loads of Data☆20Updated 7 years ago
- Content for the Model Interpretability Tutorial at Pycon US 2019☆41Updated 5 months ago