A Bayesian Workflow with PyMC and ArviZ
Corrie Bartelheimer
Data Science, Statistics

An Example of a Bayesian Workflow using PyMC and ArviZ: Predicting House Prices in Berlin

Active Learning with Bayesian Nonnegative Matrix Factorization for Recommender Systems
Gönül Aycı

An approach for a matrix completion problem using the Bayesian Nonnegative Matrix Factorization (NMF).

Automated Feature Engineering and Selection in Python
Franziska Horn
Data Science, Machine Learning, Science, Data Engineering, Statistics

Automated feature engineering and selection in Python with the autofeat library.

Embrace uncertainty! Why to go beyond point estimators for valuable ML applications
Stefan Maier
Algorithms, Data Science, Machine Learning, Statistics

Usually, uncertainties of Machine Learning predictions are just regarded as a sign of poor prediction accuracy or as a consequence of lacking input features. This talk illustrates how modeling uncertainties can improve ML based decisions.

Extended Ligthning Talks CANCELLED: Crunching Numbers Like a Journalist
Marie-Louise Timcke
Big Data, Data Science, Statistics

Marie will talk about how newsrooms work with data on a day to day basis, and how scientific accuracy fits in with the pace of news reporting.

Friend or Foe: Comparison of R & Python in Data Wrangling & Visualisation
Yuta Kanzawa
Data Science, Machine Learning, Visualisation, Statistics

R and Python are different in community and as language. Still, comparing them in their common fields such as data wrangling and visualisation, useRs and Pythonistas will deepen mutual understanding.

Gaussian Process for Time Series Analysis
Dr. Juan Orduz
Algorithms, Data Science, Machine Learning, Statistics

Gaussian process for regressions problems and time series forecasting

Gaussian Progress
Vincent Warmerdam
Artificial Intelligence, Algorithms, Data Science, IDEs/ Jupyter, Machine Learning, Statistics

gaussian progress. it's meta, but also the most normal conference title this year!

Hidden Markov Models for Chord Recognition - Intuition and Applications
Caio Miyashiro
Algorithms, Data Science, Machine Learning, Statistics

Come check out Caio's workshop on music+programming+stats on PyData

Leveraging ML to obtain fine-grained (yet reliable) causal estimates from A/B tests and experiments
Maximilian Eber
Data Science, Machine Learning, Science, Statistics

How to use machine learning to evaluate randomised experiments and A/B tests

Leveraging the advantages of Bayesian Methods to build a data science product using PyMC3
Korbinian Kuusisto
Algorithms, Business & Start-Ups, Data Science, Machine Learning, Science, Statistics

How can one leverage the power of Bayesian methods to build a successful data science product?

Loss Function Theory 101
David Wölfle
Artificial Intelligence, Algorithms, Deep Learning, Data Science, Machine Learning, Statistics

This talk covers the theoretical background behind two common loss functions, mean squared error and cross entropy, including why they are used for machine learning at all, and what limitations you should keep in mind.

Should I stay or should I go? Optimal exercise decisions using the Longstaff-Schwartz algorithm
Benedikt Rudolph
Algorithms, Business & Start-Ups, Data Science, Science, Statistics

Learn about a simple least-squares approach to evaluate financial exercise options and make optimal exercise decisions.

Time series modelling with probabilistic programming
Sean Matthews, Jannes Quer
Data Science, Statistics

Probabilistic time-series forecasting @ Deloitte Analytics Institute

Why you don’t see many real-world applications of Reinforcement Learning.
Yurii Tolochko
Artificial Intelligence, Algorithms, Deep Learning, Machine Learning, Statistics

Why doesn’t RL show the same success as (un)supervised learning? Inherent difficulties facing RL and avenues for future work