Andy Petrella
where else to find them
what they talk about
all 6 in the filters
where they keep going back
no series more than once — all 4 in the filters
on a stage with
- Dean Wampler2×
- Melanie Warrickonce
- Rand Hindionce
all 4 in the filters
who talks about the same things
- Dean Wampler29 talks
- Xavier Tordoir4 talks
- Oleg Klimenko4 talks
- Holden Karau39 talks
- Frank Munz8 talks
- Matei Zaharia30 talks
| title | conference | date |
|---|---|---|
| What Is Data Observability and What Benefits Does It Bring to Data Teams? | Voxxed Days Luxembourg 2022 | 2022-06-21 |
Data observability is presented as a way for data teams to monitor in real time how data is used across systems, projects, and applications so they can detect… | ||
| Deep Learning and NLP with Spark | Scala Days Berlin 2016 | 2016-06-15 |
Implements an LSTM sentiment classifier on Spark using DL4J, ND4J and the Google News word2vec (binary, expands to ~3.5 GB in memory) to convert IMDb reviews… | ||
| Scala: The Unpredicted Lingua Franca for Data Science | Scala Days Berlin 2016 | 2016-06-15 |
Argument: Scala gains traction because JVM deployment, functional closures and Spark let teams run distributed analytics without language gaps; claim includes… | ||
| Deep Learning and NLP with Spark | Scala Days Berlin 2016 | 2016-06-15 |
Implements a Spark‑ready LSTM used for sentiment on IMDB reviews, training a two‑layer LSTM with 200 cells fed by 300‑dim word vectors and batched at 50… | ||
| Scala: The Unpredicted Lingua Franca for Data Science | Scala Days Berlin 2016 | 2016-06-15 |
Claims Scala becomes the practical engine behind distributed data science by enabling interactive, production-ready workflows using Spark Notebook and Docker… | ||
| DBTB INT Andy Petrella | Data By the Bay 2016 | 2016-05-16 |
A platform for interoperable, scalable genomics and health data that moves teams from ad hoc analysis to production-ready pipelines by pushing curated datasets… | ||
| Interactive Machine Learning on Genomics Data with Spark Notebook | Data By the Bay 2016 | 2016-05-16 |
Converts 1000 Genomes BAM/VCF raw files (≈152 GB) into ADAM schema stored as Parquet, creating ~10,000 partitions so the same dataset loads in about one minute… | ||
| A Scalable GA4GH Server Implementation | Data By the Bay 2016 | 2016-05-16 |
A GA4GH server implementation that claims to be a scalable reference uses Apache Spark and the ADAM genomics schemas as its back end, implements variant… | ||
| Large Road-Network analysis with GraphX | Scala.IO 2014 | 2014-10-23 |
Uses GraphX on Spark to turn OpenStreetMap ways into a dual road graph (sections between intersections), processes ~80 cities totaling ~3 million section-edges… | ||
| Scalable Genomics with ADAM | Scala.IO 2014 | 2014-10-23 |
ADAM is a schema‑first storage and processing stack built on Apache Spark and Parquet that replaces bulky VCF text files with typed columnar rows, reducing… | ||
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