What we're about

Building Scalable Predictive Data Pipelines.
Data DevOps way of realizing the Data Pipelines.

We care about trends, tools, languages, platforms, practices, patterns, frameworks that aid in solution-ing, designing, architect-ing, developing, implementing, deploying, maintaining scalable Predictive Data Pipelines.

The list will only give a glimpse of areas we care about, but the list can go really long..
Ingestion, Cleansing, EDA, Feature Engineering, Statistical Analysis, Model Building, Auto Training/Re-Training, Model Performance monitoring, Dash-boarding Model Predictions, Pattern Recognition and so on.

Crunching variety of data kinds and building Pipelines around -
tabular, semi-structured, time-series, streams, images, audio/speech, video, graphData, text, geoData etc

This is open to any data enthusiasts.

First meeting will be an introduction and setting the expectations for this meetup.
The moderator will pick a topic for the next meetup based on majority vote. Members are requested to come with topics of interest.

Example Topics can be as follows-

Kubernetes based Data Processing/ML frameworks.
Building a basic Fraud Detection DataPipeline on Stream Data.
Best Practices in building a scalable Data Pipelines.
Building a Fault tolerant Data Pipeline Stages.
Raise of Functional Languages/Functional Constructs for Distributed Systems.
Building a text summarization pipeline.
Product-ionizing a deep learning model.
Picking a language for Predictive Pipelines.
Building Docker Images for ML solutions.

Meetup will be more discussion-based rather than instruction-based because of sheer vastness of the area we are indulging in.

We can do demos, discussions, teaching, compete/debate on solution-ing/architect-ing Data Pipelines. Any new ideas are appreciated.

Upcoming events

No upcoming events