NYU Center for Data Science

JULY 18, 2023

Their work specializes in signal processing and inverse problems, machine learning and deep learning, and high-dimensional statistics and probability. And how can we best use insights from natural intelligence to develop new, more powerful machine intelligence technologies that more fruitfully interact with us?”

Data Science 98

Data Science Machine Learning Machine Learning Natural Language Processing 98

AWS Machine Learning Blog

OCTOBER 5, 2023

He focuses on developing scalable machine learning algorithms. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering. Yida Wang is a principal scientist in the AWS AI team of Amazon.

AWS 130

AWS Machine Learning Machine Learning Deep Learning 130

Dataconomy

JANUARY 24, 2024

The company is renowned for its deep understanding of machine learning and natural language processing technologies, providing practical AI solutions tailored to businesses’ unique needs. Their team of AI experts excels in creating algorithms for deep learning, predictive analytics, and automation.

AI 113

AI AI Predictive Analytics Machine Learning 113

AWS Machine Learning Blog

APRIL 18, 2023

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

ML 96

ML ML Deep Learning Deep Learning 96

AWS Machine Learning Blog

JANUARY 30, 2023

Problem statement Machine learning has become an essential tool for extracting insights from large amounts of data. From image and speech recognition to natural language processing and predictive analytics, ML models have been applied to a wide range of problems. The processed data takes 8.5 2 3175 3294 0.94

Algorithm 106

Algorithm Clustering Machine Learning Machine Learning 106

AWS Machine Learning Blog

APRIL 18, 2023

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

ML 52

ML ML Deep Learning Deep Learning 52

DagsHub

DECEMBER 23, 2024

  Overview of the types of active learning | Source : Settles, B. Active Learning Literature Survey Pool-Based Active Learning Overview Pool-based active learning is the most commonly used approach in practical applications.   Traditional Active Learning has the following characteristics.

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Clustering 52