Towards AI

JULY 23, 2023

In the first part of the series, we talked about how Transformer ended the sequence-to-sequence modeling era of Natural Language Processing and understanding. Semi-Supervised Sequence Learning As we all know, supervised learning has a drawback, as it requires a huge labeled dataset to train.

Natural Language Processing 73

Natural Language Processing Supervised Learning Deep Learning Deep Learning 73

Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy.

Natural Language Processing 83

Natural Language Processing Supervised Learning Machine Learning Machine Learning 83

Hacker News

MARCH 25, 2022

Transformers made self-supervised learning possible, and AI jumped to warp speed,” said NVIDIA founder and CEO Jensen Huang in his keynote address this week at GTC. Transformers are in many cases replacing convolutional and recurrent neural networks (CNNs and RNNs), the most popular types of deep learning models just five years ago.

Machine Learning 182

Machine Learning Machine Learning AI AI 182

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. read HTML).

Data Preparation 91

Data Preparation AI AI Database 91

Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. During the training process, the model accepts sequences of words with one or more words missing. The model then predicts the missing words (see “what is self-supervised learning?”

Natural Language Processing 52

Natural Language Processing Python Machine Learning Machine Learning 52

Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. During the training process, the model accepts sequences of words with one or more words missing. The model then predicts the missing words (see “what is self-supervised learning?”

Natural Language Processing 52

Natural Language Processing Python Machine Learning Machine Learning 52

Kaggle

JULY 29, 2020

[link] David Mezzetti is the founder of NeuML, a data analytics and machine learning company that develops innovative products backed by machine learning. In August 2019, Data Works was acquired and Dave worked to ensure a successful transition. What supervised learning methods did you use?

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ETL Data Scientist Machine Learning Machine Learning 71