PyData

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PyData is a gathering of users and developers of data analysis tools in Python. PyData aims to provide Python enthusiasts a place to share ideas and learn from each other about how best to apply our language and tools to ever-evolving challenges in the vast realm of data management, processing, analytics, and visualization. We aim to be an accessible, community-driven conference, with tutorials for novices, advanced topical workshops for practitioners, and opportunities for package developers and users to meet in person.

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Aktuellste Beliebteste SlideShares

Deprecating the state machine: building conversational AI with the Rasa stack - Justina Petraitytė

Vor 5 Jahren • 3628 Aufrufe

Towards automating machine learning: benchmarking tools for hyperparameter tuning - Dr. Thorben Jensen

Vor 5 Jahren • 1153 Aufrufe

Using GANs to improve generalization in a semi-supervised setting - trying it in open datasets - Andreas Merentitis, Carmine Paolino, Vaibhav Singh

Vor 5 Jahren • 852 Aufrufe

PyData

Deprecating the state machine: building conversational AI with the Rasa stack - Justina Petraitytė

Towards automating machine learning: benchmarking tools for hyperparameter tuning - Dr. Thorben Jensen

Using GANs to improve generalization in a semi-supervised setting - trying it in open datasets - Andreas Merentitis, Carmine Paolino, Vaibhav Singh

LightFields.jl: Fast 3D image reconstruction for VR applications - Hector Andrade Loarca

Extracting relevant Metrics with Spectral Clustering - Evelyn Trautmann

GDPR in practise - Developing models with transparency and privacy in mind - Łukasz Mokrzycki

From cells to drug responses - machine learning in cancer research - Julian de Ruiter, Nanne Aben

Thompson Sampling for Machine Learning - Ruben Mak

Python and the Holy Grail of Causal Inference - Dennis Ramondt, Huib Keemink

Learning credit networks with applications in financial industry - Sumit Sourabh

Who's singing? Automatic bird sound recognition with machine learning - Dan Stowell

Unsupervised Anomaly Detection with Isolation Forest - Elena Sharova

Diamond mixed effects models in Python

Git risky using git metadata to predict code bug risk

Random Forests Best Practices for the Business World

Asynchronous Python A Gentle Introduction

Data Science Keys to Open Up OpenNASA Datasets

BeakerX Beaker Extensions for Jupyter

Simplifying And Accelerating Data Access for Python With Dremio and Apache Arrow

Managing python at scale without breaking the bank