(…) Ultralytics open-source research into future object detection methods, and incorporates our lessons learned and best practices evolved over training thousands of models on custom client datasets with our previous YOLO repository https://github.com/ultralytics/yolov3. All code and models are under active development, and are subject to modification or deletion without notice. Use at your own risk.
https://github.com/ultralytics/yolov5
Category Archives: Big Data
AI & Machine Learning Products
InsideAirBNB
grablab.org – Web Scraping and Data Processing Services
No More Google
No More Google
Privacy-friendly alternatives to Google that don’t track you
https://nomoregoogle.com
Facebook data
bigdata – Global Science Research (GSR)
About us
Global Science Research (GSR) was founded to optimize marketing strategies with the power of big data and psychological sciences. Our innovative methods produce insight on a revolutionary scale, empowering clients to understand consumers, markets, and competitors more deeply and accurately than ever before. GSR’s team is formed of experienced business analysts and leading academics, all of whom are experienced in helping companies utilize the power of psychology in the customer journey. Our innovative methods produce consumer insight on a revolutionary scale, empowering our clients to understand their consumers, markets, and competitors more deeply and accurately than ever before.
https://www.linkedin.com/company/global-science-research/
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The Infrastructure Behind Twitter: Scale
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Hadoop: We have multiple clusters storing over 500 PB divided in four groups (real time, processing, data warehouse and cold storage). Our biggest cluster is over 10k nodes. We run 150k applications and launch 130M containers per day.
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Manhattan(the backend for Tweets, Direct Messages, Twitter accounts, and more): We run several clusters for different use cases such as large multi tenant, smaller for non common, read only, and read/write for heavy write/heavy read traffic patterns. The read/only cluster handles 10s of millions QPS whereas a read/write cluster handles millions of QPS. The highest performance cluster, our observability cluster, which ingests in every datacenter, handles over tens of million writes.
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Graph: Our legacy Gizzard/MySQL based sharded cluster for storing our graphs. Flock, our social graph, can manage peaks over tens of million QPS, averaging our MySQL servers to 30k – 45k QPS.
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Blobstore: Our image, video and large file store where we store hundreds of billions objects.
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Cache: Our Redis and Memcache clusters: caching our users, timelines, tweets and more.
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SQL: This includes MySQL, PostgreSQL and Vertica. MySQL/PosgreSQL are used where we need strong consistency, managing ads campaign, ads exchange as well as internal tools. Vertica is a column store often used as a backend for Tableau supporting sales and user organisations.