Data Science 101

OCTOBER 12, 2023

The first project we did used NLP for finance contracts (this was 2016). I mostly use U-SQL, a mix between C# and SQL that can distribute in very large clusters. Once the data is processed I do machine learning: clustering, topic finding, extraction, and classification. So you use a lot of the Azure tools in your job?

Azure 64

Azure Computer Science Computer Science Clustering 64

AWS Machine Learning Blog

SEPTEMBER 11, 2024

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. The State of AI Report gives the size and owners of the largest A100 clusters, the top few being Meta with 21,400, Tesla with 16,000, XTX with 10,000, and Stability AI with 5,408.

AWS 113

AWS ML ML Clustering 113

phData

NOVEMBER 8, 2024

Partitioning and clustering features inherent to OTFs allow data to be stored in a manner that enhances query performance. Cost Efficiency and Scalability Open Table Formats are designed to work with cloud storage solutions like Amazon S3, Google Cloud Storage, and Azure Blob Storage, enabling cost-effective and scalable storage solutions.

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

Pickl AI

AUGUST 22, 2024

First released in 2016, it quickly gained traction due to its intuitive design and robust capabilities. Scalability TensorFlow can handle large datasets and scale to distributed clusters, making it suitable for training complex models. Read More: Unlocking Deep Learning’s Potential with Multi-Task Learning.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52