Version 0.30 Nov. 9, 2022
We released a new schedule version!
We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:
- “Fireside Chat with Tom Caswell” (Nov. 10, 2022, 11:45 a.m. → Nov. 10, 2022, 1:30 p.m.)
- “Fireside Chat with Melissa Mendonça” (Nov. 10, 2022, 1:30 p.m. → Nov. 10, 2022, 11:45 a.m.)
Version 0.29 Nov. 6, 2022
We released a new schedule version!
Version 0.28 Nov. 2, 2022
We released a new schedule version!
We have a new session: “NumFOCUS Champions Circle presents: How to make friends and generate impact through open source communities” by Lauren Oldja .
Version 0.27 Nov. 2, 2022
We released a new schedule version!
We have a new session: “Open Source Project Sprints” by conda/conda-forge, PyMC, NumPy/SciPy, & Matplotlib .
Version 0.26 Nov. 2, 2022
We released a new schedule version!
We have new sessions!
Version 0.25 Nov. 2, 2022
We released a new schedule version!
We have a new session: “Lightning Talks” .
Version 0.24 Nov. 2, 2022
We released a new schedule version!
We have a new session: “CodeDuel Finals” .
Version 0.23 Nov. 1, 2022
We released a new schedule version!
We have new sessions!
Version 0.22 Nov. 1, 2022
We released a new schedule version!
Version 0.21 Nov. 1, 2022
We released a new schedule version!
We have new sessions!
Version 0.20 Oct. 31, 2022
We released a new schedule version!
Version 0.19 Oct. 25, 2022
We released a new schedule version!
We have a new session: “PyScript & Data Science: PyData stack on the Browser” by Fabio Pliger .
Version 0.18 Oct. 20, 2022
We released a new schedule version!
We have a new session: “pandas at a Crossroads, the Past, Present, and Future” by Jeff Reback .
We have moved a session around: “Why do I need to know Python? I'm a pandas user…” by James Powell (Nov. 10, 2022, 11 a.m., Central Park West (6th floor) → Nov. 9, 2022, 3:30 p.m., Radio City (6th floor)).
Version 0.17 Oct. 20, 2022
We released a new schedule version!
Version 0.16 Oct. 19, 2022
We released a new schedule version!
We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:
- “Ibis: Expressive analytics in Python at any scale.” by Gil Forsyth, Charles Cloud (Radio City (6th floor) → Central Park West (6th floor))
- “Contextual Multi-Arm Bandit and its applications to digital experiments” by Li Qin, Reed Peterson (Central Park West (6th floor) → Radio City (6th floor))
Version 0.15 Oct. 12, 2022
We released a new schedule version!
We have a new session: “Supercharge your Python code with Blocks” by Jeff Hale .
Version 0.14 Oct. 5, 2022
We released a new schedule version!
Version 0.13 Oct. 5, 2022
We released a new schedule version!
Version 0.12 Oct. 4, 2022
We released a new schedule version!
We have new sessions!
- “Holistic MLOps for better science”
- “Practical MLOps: Do we need all the things?”
- “Building highload ML powered service”
We have moved a session around: “Deploying Dask” by Matthew Rocklin (Nov. 10, 2022, 11:45 a.m. → Nov. 9, 2022, 3:30 p.m.)
Version 0.11 Oct. 3, 2022
We released a new schedule version!
We sadly had to cancel a session: “Explaining Explainable AI tools : Issues, Pitfalls and Cautionary Tales” by Aditya Lahiri.
Version 0.10 Oct. 2, 2022
We released a new schedule version!
We have a new session: “Discover Inspirational Insights in Motivational Sports Speeches Using Speech-to-Text” by Tonya Sims .
Version 0.9 Oct. 2, 2022
We released a new schedule version!
Version 0.8 Oct. 2, 2022
We released a new schedule version!
We have a new session: “Using Interconnected ML Models to Tackle Retail Challenges” by Kshetrajna Raghavan .
Version 0.7 Oct. 1, 2022
We released a new schedule version!
Version 0.6 Oct. 1, 2022
We released a new schedule version!
Version 0.5 Oct. 1, 2022
We released a new schedule version!
Version 0.4 Oct. 1, 2022
We released a new schedule version!
Version 0.3 Oct. 1, 2022
We released a new schedule version!
We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:
- “Install Python. Quarto Render All the Things” by Daniel Chen (Nov. 10, 2022, 1:30 p.m., Central Park West (6th floor) → Nov. 9, 2022, 11:45 a.m., Central Park East (6th floor))
- “Deep learning for time series forecasting and classification in practice” by Isaac Godfried (Nov. 11, 2022, 9 a.m. → Nov. 11, 2022, 11 a.m.)
- “CATs: Content-Addressable Transformers” by Joshua E. Jodesty (Nov. 10, 2022, 11:45 a.m. → Nov. 10, 2022, 2:15 p.m.)
- “Simulations in Python: Discrete Event Simulation with SimPy” by Lara Kattan (Nov. 9, 2022, 11 a.m., Central Park East (6th floor) → Nov. 9, 2022, 4:15 p.m., Central Park West (6th floor))
- “Large Language Models for Real-World Applications - A Gentle Intro” by Hemant Jain (Nov. 10, 2022, 2:15 p.m., Central Park West (6th floor) → Nov. 10, 2022, 11:45 a.m., Central Park East (6th floor))
- “20 ideas to build social capital in the Data Science ecosystem” by Lawrence Wilson Gray (Nov. 10, 2022, 1:30 p.m., Winter Garden (5th floor) → Nov. 10, 2022, 10:15 a.m., Central Park West (6th floor))
- “How we upstreamed our internal goals to JupyterLab 4” by Diego Torres Quintanilla (Nov. 10, 2022, 10:15 a.m. → Nov. 10, 2022, 2:15 p.m.)
- “Fairness for Scikit-Learn Pipelines with Lale” by Martin Hirzel (Nov. 9, 2022, 4:15 p.m., Central Park West (6th floor) → Nov. 9, 2022, 10:15 a.m., Radio City (6th floor))
- “Distributed Python with Ray: Hands on with the Ray 2.0 APIs for scaling Python Workloads” by Jules S. Damji (Central Park West (6th floor) → Central Park East (6th floor))
- “Expressive and fast dataframes in Python with polars” by Juan Luis (Nov. 9, 2022, 2:45 p.m., Central Park West (6th floor) → Nov. 9, 2022, 11 a.m., Central Park East (6th floor))
- “ipyvizzu-story - a new, open-source tool to build, create and share animated data stories with Python in Jupyter” by Peter Vidos (Nov. 11, 2022, 3:30 p.m., Winter Garden (5th floor) → Nov. 11, 2022, 9 a.m., Music Box (5th floor))
- “Level up your viz skills: from Matplotlib to HoloViz” by Sophia Yang (Nov. 10, 2022, 11 a.m. → Nov. 9, 2022, 2:45 p.m.)
- “Building a Semantic Search Engine” by Mustafa Zengin, nidhin pattaniyil, Ravi, Vishal Rathi (Nov. 11, 2022, 1:30 p.m., Winter Garden (5th floor) → Nov. 11, 2022, 11 a.m., Central Park East (6th floor))
- “Serving Pytorch Models in Production” by Dagshayani Kamalaharan, nidhin pattaniyil (Nov. 11, 2022, 11 a.m., Central Park East (6th floor) → Nov. 11, 2022, 1:30 p.m., Central Park West (6th floor))
- “Scaling Python - Bank Edition” by Anirrudh Krishnan, Andrew Fulton, Adam Lewis (Nov. 9, 2022, 11:45 a.m., Central Park West (6th floor) → Nov. 10, 2022, 2:15 p.m., Central Park East (6th floor))
- “A Guide to Data Science as a Creative Discipline” by Ilinca Barsan (Nov. 9, 2022, 4:15 p.m., Central Park East (6th floor) → Nov. 9, 2022, 11 a.m., Central Park West (6th floor))
- “Model Upgrade Schemes: Considerations for Updating Production Models” by Emmanuel Naziga, Munaf A Qazi (Nov. 10, 2022, 11:45 a.m., Central Park East (6th floor) → Nov. 10, 2022, 1:30 p.m., Winter Garden (5th floor))
- “Contextual Multi-Arm Bandit and its applications to digital experiments” by Li Qin, Reed Peterson (Radio City (6th floor) → Central Park West (6th floor))
- “Improving Your Data Modeling Work Through Open-Source Software” by Ido Michael, Eduardo Blancas (Nov. 11, 2022, 1:30 p.m. → Nov. 11, 2022, 9 a.m.)
- “Implementing a Workflow Engine in Python” by Sanjay Siddhanti (Nov. 9, 2022, 10:15 a.m., Music Box (5th floor) → Nov. 10, 2022, 11:45 a.m., Winter Garden (5th floor))
- “Testing Big Data Applications (Spark, Dask, and Ray)” by Han Wang (Nov. 9, 2022, 10:15 a.m. → Nov. 10, 2022, 1:30 p.m.)
- “Explaining Explainable AI tools : Issues, Pitfalls and Cautionary Tales” by Aditya Lahiri (Nov. 9, 2022, 11 a.m., Music Box (5th floor) → Nov. 9, 2022, 3:30 p.m., Central Park West (6th floor))
- “Bagging to BERT: A tour of applied NLP” by Benjamin Batorsky (Central Park East (6th floor) → Winter Garden (5th floor))
- “Fast and Scalable Timeseries Modelling with Fugue and Nixtla” by Kevin Kho (Nov. 11, 2022, 11 a.m. → Nov. 11, 2022, 1:30 p.m.)
- “Herding Entities: Information Search and Synthesis in the Context of Transaction Data” by Marcin Ziemiński (Central Park East (6th floor) → Winter Garden (5th floor))
- “Human-Friendly, Production-Ready Data Science Stack with Metaflow & Kubernetes” by Savin Goyal (Nov. 9, 2022, 2:45 p.m. → Nov. 10, 2022, 1:30 p.m.)
- “High-Dimensional Data Visualizations with MDS, t-SNE, and UMAP” by Michalis Xyntarakis (Nov. 11, 2022, 9 a.m., Music Box (5th floor) → Nov. 11, 2022, 3:30 p.m., Winter Garden (5th floor))
- “Zeno Does Data Science: The Paradoxical Quest for Reproducibility” by Kjell Wooding (Nov. 9, 2022, 10:15 a.m., Winter Garden (5th floor) → Nov. 9, 2022, 2:45 p.m., Central Park East (6th floor))
- “Shiny for Python: Interactive apps and dashboards made easy-ish” by Joe Cheng (Nov. 9, 2022, 11:45 a.m. → Nov. 9, 2022, 4:15 p.m.)
- “Ibis: Expressive analytics in Python at any scale.” by Gil Forsyth, Charles Cloud (Nov. 9, 2022, 11 a.m., Central Park West (6th floor) → Nov. 9, 2022, 11:45 a.m., Radio City (6th floor))
- “Why do I need to know Python? I'm a pandas user…” by James Powell (Nov. 10, 2022, 11:45 a.m., Winter Garden (5th floor) → Nov. 10, 2022, 11 a.m., Central Park West (6th floor))
- “Causal machine learning for a smart paywall at The New York Times” by Rohit Supekar (Nov. 9, 2022, 3:30 p.m. → Nov. 9, 2022, 10:15 a.m.)
Version 0.2 Sept. 30, 2022
We released a new schedule version!
We have new sessions!
- “Install Python. Quarto Render All the Things”
- “Deep learning for time series forecasting and classification in practice”
- “Dask”
- “Git for Data: Data Versioning for Reproducible Data Science with Dolt”
- “CATs: Content-Addressable Transformers”
- “Simulations in Python: Discrete Event Simulation with SimPy”
- “Predicting Weather-Caused Rare Events: A Utility Outage Prediction Use Case”
- “Large Language Models for Real-World Applications - A Gentle Intro”
- “How to build a serverless electricity price prediction service in just Python with Hopsworks and Streamlit”
- “20 ideas to build social capital in the Data Science ecosystem”
- “How we upstreamed our internal goals to JupyterLab 4”
- “Troubleshooting your Data Workflows with Noteable + Dagster: A live debugging of failed jobs.”
- “Turning Data/AI algorithms into production-ready applications in no time with Taipy, the next-gen Python application builder”
- “Coldstart: A library for automatic data curation and feature engineering”
- “Fairness for Scikit-Learn Pipelines with Lale”
- “Using Numba Effectively Today”
- “Why do I need to know Python? I'm a pandas user…”
- “Distributed Python with Ray: Hands on with the Ray 2.0 APIs for scaling Python Workloads”
- “Data and Model Version Control: Applications in ML Drug Discovery pipelines”
- “ipyvizzu-story - a new, open-source tool to build, create and share animated data stories with Python in Jupyter”
- “Parallelism in Numerical Python Libraries”
- “Level up your viz skills: from Matplotlib to HoloViz”
- “Building a Semantic Search Engine”
- “Serving Pytorch Models in Production”
- “Scaling Python - Bank Edition”
- “Scalable Feature Engineering with Hamilton”
- “I hate writing tests, that's why I use Hypothesis”
- “Causal machine learning for a smart paywall at The New York Times”
- “A Guide to Data Science as a Creative Discipline”
- “Apache Beam on Dask: Portable, Scalable, Scientific Python (AKA Data Engineering for the Climate)”
- “Model Upgrade Schemes: Considerations for Updating Production Models”
- “Contextual Multi-Arm Bandit and its applications to digital experiments”
- “NixtlaVerse, bridging the gap between statistics and deep learning for time series.”
- “Improving Your Data Modeling Work Through Open-Source Software”
- “Gentle introduction to scaling up ML service with Kubernetes + Mlflow”
- “Chasing the Overton Window”
- “Deploying Dask”
- “Implementing a Workflow Engine in Python”
- “Testing Big Data Applications (Spark, Dask, and Ray)”
- “Explaining Explainable AI tools : Issues, Pitfalls and Cautionary Tales”
- “Bagging to BERT: A tour of applied NLP”
- “Nebari: Easily deploy and maintain an open source data science platform on the cloud of your choice”
- “Introduction to Causal Inference”
- “Fast and Scalable Timeseries Modelling with Fugue and Nixtla”
- “ML Latency No More: Useful Patterns to Reduce ML Prediction Latency to Sub X ms”
- “Herding Entities: Information Search and Synthesis in the Context of Transaction Data”
- “Human-Friendly, Production-Ready Data Science Stack with Metaflow & Kubernetes”
- “Customizable probabilistic record linkage with Name Match”
- “High-Dimensional Data Visualizations with MDS, t-SNE, and UMAP”
- “Hands-On Computer Vision with PyTorch”
- “JAX for Bayes”
- “Zeno Does Data Science: The Paradoxical Quest for Reproducibility”
- “Shiny for Python: Interactive apps and dashboards made easy-ish”
- “Prompt Engineering ⚙️ - Addressing the sensitivity of Large language models”
- “Ibis: Expressive analytics in Python at any scale.”
- “Understanding the News around the World with Web Scraping and NLP at Scale”
- “A Graph-based Machine Learning early warning system to detect Ransomware”
- “Expressive and fast dataframes in Python with polars”
Version 0.1 Sept. 29, 2022
We released our first schedule!