Explosion

APRIL 1, 2017

We wrote this post while working on Prodigy , our new annotation tool for radically efficient machine teaching. Prodigy features many of the ideas and solutions for data collection and supervised learning outlined in this blog post. It’s a cloud-free, downloadable tool and comes with powerful active learning models.

Supervised Learning 40

Supervised Learning Machine Learning Machine Learning Algorithm 40

Hacker News

MAY 3, 2023

We are going to explore these and other essential questions from the ground up , without assuming prior technical knowledge in AI and machine learning. The core process is a general technique known as self-supervised learning , a learning paradigm that leverages the inherent structure of the data itself to generate labels for training.

Supervised Learning 181

Supervised Learning Natural Language Processing AI AI 181

Applied Data Science

MARCH 11, 2022

In contrast to classification, a supervised learning paradigm, generation is most often done in an unsupervised manner: for example an autoencoder , in the form of a neural network, can capture the statistical properties of a dataset. One does not need to look into the math to see that it’s inherently more difficult.

AI 130

AI AI Data Science Machine Learning 130

AWS Machine Learning Blog

AUGUST 16, 2023

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. One way to overcome this challenge is through self-supervised learning (SSL). Machine Learning Engineer at AWS. Andrew Ang is a Sr.

ML 98

ML ML Data Scientist AWS 98

Snorkel AI

MARCH 1, 2023

Foundation Models (FMs), such as GPT-3 and Stable Diffusion, mark the beginning of a new era in machine learning and artificial intelligence. Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning?

Natural Language Processing 83

Natural Language Processing Supervised Learning Machine Learning Machine Learning 83

Explosion

AUGUST 3, 2017

Machine learning systems are built from both code and data. That’s why we’re pleased to introduce Prodigy , a downloadable tool for radically efficient machine teaching. Machine learning is an inherently uncertain technology, but the waterfall annotation process relies on accurate upfront planning.

Supervised Learning 52

Supervised Learning Python Machine Learning Machine Learning 52

AWS Machine Learning Blog

AUGUST 7, 2023

The Transformer architecture 3 (Vaswani, 2017) was a breakthrough improvement on the encoder-decoder; it introduced the concept of self-attention , which allowed the model to focus its attention on different words on the input and output phrases.

AWS 98

AWS ML ML Data Science 98

Heartbeat

JULY 20, 2023

Limited availability of labeled datasets: In some domains, there is a scarcity of datasets with fine-grained annotations, making it difficult to train segmentation networks using supervised learning algorithms. When evaluated on the MS COCO dataset test-dev 2017, YOLOv8x attained an impressive average precision (AP) of 53.9%

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Mlearning.ai

JULY 31, 2023

2017) paper, vector embeddings have become a standard for training text-based DL models. Data2Vec: A General Framework For Self-Supervised Learning in Speech, Vision and Language. It is none other than the legendary Vector Embeddings! Without further ado, let’s dive right in! A vector embedding is an object (e.g., and Auli, M.,

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Algorithm 52

Mlearning.ai

AUGUST 6, 2023

Towards the end of my studies, I incorporated basic supervised learning into my thesis and picked up Python programming at the same time. I also started on my data science journey by attending the Coursera specialization by Andrew Ng —  Deep Learning. That was in 2017. Getting the first job was the hardest.

Data Science 52

Data Science Machine Learning Machine Learning ML 52

Google Research AI blog

JANUARY 18, 2023

I will begin with a discussion of language, computer vision, multi-modal models, and generative machine learning models. Language Models The progress on larger and more powerful language models has been one of the most exciting areas of machine learning (ML) research over the last decade.

ML 132

ML ML AI AI 132

Flipboard

APRIL 4, 2025

Supervised learning can help tune LLMs by using examples demonstrating some desired behaviors, which is called supervised fine-tuning (SFT). 2017) provided the first evidence that RLHF could be economically scaled up to practical applications. 2017) Deep reinforcement learning from human preferences.

AI 148

AI AI Algorithm Artificial Intelligence 148

Data Science Blog

MARCH 14, 2023

Von Data Science spricht auf Konferenzen heute kaum noch jemand und wurde hype-technisch komplett durch Machine Learning bzw. GPT-3 ist jedoch noch komplizierter, basiert nicht nur auf Supervised Deep Learning , sondern auch auf Reinforcement Learning. Artificial Intelligence (AI) ersetzt.

Big Data 147

Big Data Big Data Apache Hadoop Data Science 147