datapine

AUGUST 14, 2019

Companies surely need data scientists to help them empower their analytics processes, build a numbers-based strategy that will boost their bottom line, and ensure that enormous amounts of data are translated into actionable insights. Geet our bite-sized free summary and start building your data skills! R (And RStudio).

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

DataRobot Blog

APRIL 21, 2022

Machine learning, and especially deep learning, has become increasingly more accurate in the past few years. This increase in accuracy is important to make AI applications good enough for production , but there has been an explosion in the size of these models. Why should you care?

Deep Learning 145

Deep Learning Machine Learning Metrics Measurement 145

AWS Big Data

SEPTEMBER 19, 2023

This post discusses how Chime utilizes AWS Glue , Amazon Kinesis , Amazon DynamoDB , and Amazon SageMaker to build an online, serverless fraud detection solution — the Chime Streaming 2.0 Solution overview The following diagram illustrates the design of the Chime Streaming 2.0

Analytics 109

Analytics Risk Big Data Machine Learning 109

IBM Big Data Hub

APRIL 18, 2024

While AGI remains theoretical, organizations can take proactive steps to prepare for its arrival by building a robust data infrastructure and fostering a collaborative environment where humans and AI work together seamlessly. NLP techniques help them parse the nuances of human language, including grammar, syntax and context.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

AWS Big Data

JUNE 21, 2023

It comprises a search engine, OpenSearch, which delivers low-latency search and aggregations, OpenSearch Dashboards, a visualization and dashboarding tool, and a suite of plugins that provide advanced capabilities like alerting, fine-grained access control, observability, security monitoring, and vector storage and processing.

Metrics 98

Metrics Measurement Modeling Dashboards 98

Occam's Razor

APRIL 13, 2015

You'll be surprised at how much you learn, and, like an Easter egg hunt, the whole thing is fun all by itself. If it can't, figure out what the time from insight to action is, then optimize the data to insight process. So, if you were expecting hidden gems in a similar spirit, I'm afraid dissatisfaction will follow.

Analytics 156

Analytics Reporting Metrics Slice and Dice 156

Insight

OCTOBER 25, 2019

Image credit: [link] As the title suggests, this is a story about a question that may resonate well with many machine learning practitioners trying to build applications in the real world, where clean and annotated data on a specific problem can be sparse— How do we leverage the power of AI when we have very little data?

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Snapshot Testing Deep Learning Visualization 57