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Upcoming events (2)
This is online tech talk event, register on the website to receive join link:
With the rapid onset of the global Covid-19 Pandemic in 2020 the USA Centers for Disease Control and Prevention (CDC) quickly implemented a new Covid-19 pipeline to collect testing data from all of the USA’s states and territories, and produce multiple consumable results for federal and public agencies. They did this in under 30 days, using Apache Kafka.
Inspired by this story, we built two demonstration streaming pipelines for ingesting, storing, and visualizing public IoT data (Tidal data from NOAA, the National Oceanic and Atmospheric Administration) using multiple open source technologies. The common ingestion technologies were Apache Kafka, Apache Kafka Connect, and Apache Camel Kafka Connector, supplemented with Prometheus and Grafana for monitoring. The initial experiment used Open Distro for Elasticsearch and Kibana as the target storage and visualisation technologies, while the second experiment used PostgreSQL and Apache Superset.
In this talk we introduce each technology and the pipeline architecture, and walk through the steps followed, challenges encountered, and solutions used to build reliable and scalable pipelines, and visualize the results (including Tidal periods, ranges and locations). We compare and contrast the two approaches, focussing on exception handling, scalability, performance and monitoring, and the pros and cons of the two visualization technologies (Kibana and Superset).
This is online workshop on zoom, please register here to receive joining link: https://www.aicamp.ai/event/eventdetails/W2021102718
Join this hands-on workshop to get started with computer vision and object detection. Build your own object detection model from start to finish. Includes step-by-step instructions on data annotation and model training with your own dataset.
Object classification and localization within an image is foundational to many computer vision applications.
In this workshop, we'll cover:
* High level computer vision applications & concepts
* How to label your own dataset for object detection & computer vision
* How to train your model using a Faster R-CNN in python & detectron2 (A PyTorch based modular object detection library)
* Run the model for object detection on images & video
What you’ll need:
* A modern web browser
* A Google account for Colab.
Who should attend:
Anyone interested in computer vision! This workshop is designed to be approachable for most skill levels. Knowing some python programming will help, but it's not required. We encourage anyone who is curious to attend and ask questions!