2024 Clustering Data Preparation 
AWS Machine Learning Blog
NOVEMBER 19, 2024
This session covers the technical process, from data preparation to model customization techniques, training strategies, deployment considerations, and post-customization evaluation. Explore how this powerful tool streamlines the entire ML lifecycle, from data preparation to model deployment.
PyImageSearch
SEPTEMBER 16, 2024
Home Table of Contents Credit Card Fraud Detection Using Spectral Clustering Understanding Anomaly Detection: Concepts, Types and Algorithms What Is Anomaly Detection? By leveraging anomaly detection, we can uncover hidden irregularities in transaction data that may indicate fraudulent behavior.
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Towards AI
JULY 23, 2024
Competition at the leading edge of LLMs is certainly heating up, and it is only getting easier to train LLMs now that large H100 clusters are available at many companies, open datasets are released, and many techniques, best practices, and frameworks have been discovered and released. Why should you care?
ODSC - Open Data Science
JANUARY 29, 2024
Using skills such as statistical analysis and data visualization techniques, prompt engineers can assess the effectiveness of different prompts and understand patterns in the responses. This skill focuses on minimizing the resources and time required for an LLM to generate output based on your prompts.
PyImageSearch
OCTOBER 21, 2024
In the first part of our Anomaly Detection 101 series, we learned the fundamentals of Anomaly Detection and saw how spectral clustering can be used for credit card fraud detection. This method helps in identifying fraudulent transactions by grouping similar data points and detecting outliers. detection of potential failures or issues).
DagsHub
APRIL 21, 2024
A traditional machine learning (ML) pipeline is a collection of various stages that include data collection, data preparation, model training and evaluation, hyperparameter tuning (if needed), model deployment and scaling, monitoring, security and compliance, and CI/CD.
AWS Machine Learning Blog
SEPTEMBER 11, 2024
Learning means identifying and capturing historical patterns from the data, and inference means mapping a current value to the historical pattern. The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference.
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