PyData
11 talks in this track
Detecting and removing outliers in your data
talkAlmost every time in a data analysis, you will inevitable find the presence of unexpected or weird values in your data. The majority of statistical and machine learning algorithms will fail to converg...
ipyvizzu - a new, open-source charting tool to create animated data stories with Python in Jupyter
workshopSharing and explaining the results of your analysis can be a lot easier and much more fun when you can create an animated story of the charts containing your insights. [ipyvizzu](https://github.com/vi...
Beyond pandas: The great Python dataframe showdown
talkThe pandas library is one of the key factors that enabled the growth of Python in the Data Science industry and continues to help data scientists thrive almost 15 years after its creation. Because of ...
How I Learned to Stop Worrying and Love Python
talkThe abundance of behavioral data online and cutting-edge computational techniques seem to promise an easier way to explain and model complex human behavior. However, elegant math theories and multiple...
User-Centric Machine Learning
talkBuilding end-to-end ML systems can be challenging, especially when it's part of a complex user experience in a health app. This is a story of how a user-focused mindset and product thinking helped Flo...
It's (not) about the data!
workshopGiven the vast amount of resources we have online on becoming a data scientist, it is only natural to feel overwhelmed and lost. Those who manage to start a career in the field, eventually spend major...
Up and Down the Ladder of Experimentation
talkI am biased. I cannot stop seeing complex systems. Complex systems are characterised by many components that interact in multiple ways among each other and with their environment. That lens of comple...
Artificial Intelligence in Radiology - are we there yet?
talkDeep learning applications have been adopted widely across many industries. Radiology is no exception - it certainly can be considered a breakthrough technology. Healthcare institutions have put trust...
MLOps: challenges faced when deploying machine learning models to production
talkDeploying a machine learning model to production the right way is not a trivial task, and involves many components. This talk aims first to walk the listener through the realm of MLOps by reviewing th...
Select ML from Databases
talkThis talk introduces a new workflow for building your machine learning models using the capabilities of modern databases that support machine learning use cases natively. There is an overview of how m...
Data-driven products: from zero to hero
talkMachine learning (ML) models rarely make it to production. Often these projects start with intention ‘let’s make something cool’, but they get stuck in local Jupyter notebooks or Power Point presentat...