MinMax vs Standard vs Robust Scaler: Which One Wins for Skewed Data?
You’ve loaded your dataset and the distribution plots look rough.
How Hapag-Lloyd improved schedule reliability with ML-powered vessel schedule predictions using Amazon SageMaker
This post is cowritten with Thomas Voss and Bernhard Hersberger from Hapag-Lloyd. Hapag-Lloyd is one of the world’s leading shipping companies with more than 308 modern vessels, 11.9 million TEUs (twenty-foot equivalent units) transported per year, and 16,700 motivated employees in more than 400 offices in 139 countries. They connect continents, businesses, and people through …
Gemini CLI extension for PostgreSQL in action: Build a fuzzy search feature in minutes
Adding features to an app can be hard. One minute you’re writing code, the next you’re switching to the PostgreSQL database client to run a query, and then it’s over to the console to check on your instances. For example, let’s say you wanted to add search capabilities. This can mean adding the right extensions …
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Early Prime Day Deals: $100 Off 2 Best-Selling Espresso Makers
Ninja Luxe Cafe Premier and Breville Barista Express are the two best-selling espresso machines on Amazon. Each is $100 off.
AI model can manipulate time to make better predictions in a wide range of fields
In the world around us, many things exist in the context of time: a bird’s path through the sky is understood as different positions over a period of time, and conversations as a series of words occurring one after another.
All we got from western companies old outdated models not even open sources and false promises
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How Agentic AI Balances Compliance & Performance in Financial Services Marketing
Consumer banks and insurance companies face multiple challenges in the race to launch marketing campaigns that are both compliant with state and federal regulations, as well as high-performing. The educational infographic, Agentic AI for Marketing Compliance and Performance, explains how Agentic AI is already helping financial services marketing and legal teams overcome challenges — regulations, …
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The Model Selection Showdown: 6 Considerations for Choosing the Best Model
Selecting the right model is one of the most critical decisions in any machine learning project.
Compute-Optimal Quantization-Aware Training
Quantization-aware training (QAT) is a leading technique for improving the accuracy of quantized neural networks. Previ- ous work has shown that decomposing training into a full-precision (FP) phase followed by a QAT phase yields superior accuracy compared to QAT alone. However, the optimal allocation of compute between the FP and QAT phases remains unclear. We …
Modernize fraud prevention: GraphStorm v0.5 for real-time inference
Fraud continues to cause significant financial damage globally, with U.S. consumers alone losing $12.5 billion in 2024—a 25% increase from the previous year according to the Federal Trade Commission. This surge stems not from more frequent attacks, but from fraudsters’ increasing sophistication. As fraudulent activities become more complex and interconnected, conventional machine learning approaches fall short …
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