KDnuggets

DECEMBER 16, 2019

It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different. Gain an understanding of the important developments of the past year, as well as insights into what expect in 2020.

Artificial Intelligence 139

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 139

Google Research AI blog

APRIL 27, 2023

That is where we can use the ability of ML models to pick up on subtle intricate patterns in large amounts of data. We’ve previously demonstrated the ability to use ML models to quickly phenotype at scale for retinal diseases. We trained ML models to predict whether an individual has COPD using the full spirograms as inputs.

ML 99

ML ML Supervised Learning Deep Learning 99

AWS Machine Learning Blog

SEPTEMBER 10, 2024

As part of its goal to help people live longer, healthier lives, Genomics England is interested in facilitating more accurate identification of cancer subtypes and severity, using machine learning (ML). 2022 ) is a multi-modal ML framework that consists of three sub-network components (see Figure 1 at Chen et al.,

Supervised Learning 89

Supervised Learning Machine Learning Machine Learning AWS 89

AWS Machine Learning Blog

DECEMBER 7, 2023

Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Initially, daily forecasts for each country are formulated through ML models. His focus was building machine learning algorithms to simulate nervous network anomalies.

AWS 128

AWS Algorithm Data Science Machine Learning 128

AWS Machine Learning Blog

AUGUST 7, 2023

AWS ProServe solved this use case through a joint effort between the Generative AI Innovation Center (GAIIC) and the ProServe ML Delivery Team (MLDT). However, LLMs are not a new technology in the ML space. The new ML workflow now starts with a pre-trained model dubbed a foundation model.

AWS 94

AWS ML ML Data Science 94

AWS Machine Learning Blog

NOVEMBER 27, 2023

According to a 2019 survey by Deloitte , only 18% of businesses reported being able to take advantage of unstructured data. As AI adoption continues to accelerate, developing efficient mechanisms for digesting and learning from unstructured data becomes even more critical in the future.

Data Preparation 99

Data Preparation AI AI Python 99

Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning? Self-supervised learning is a kind of machine learning that creates labels directly from the input data. Find out in the guide below.

Natural Language Processing 83

Natural Language Processing Supervised Learning Machine Learning Machine Learning 83