Google Research AI blog

JANUARY 18, 2023

We have also seen significant success in using large language models (LLMs) trained on source code (instead of natural language text data) that can assist our internal developers, as described in ML-Enhanced Code Completion Improves Developer Productivity. language models, image classification models, or speech recognition models).

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Mlearning.ai

JUNE 22, 2023

Understanding the biggest neural network in Deep Learning Join 34K+ People and get the most important ideas in AI and Machine Learning delivered to your inbox for free here Deep learning with transformers has revolutionized the field of machine learning, offering various models with distinct features and capabilities.

Auto-classification 52

Auto-classification Auto-complete BERT Deep Learning 52

Pickl AI

JANUARY 23, 2023

This framework can perform classification, regression, etc., but performs very well with neural networks. Keras supports a high-level neural network API written in Python. Provides modularity as a series of completely configurable, independent modules that can be combined with the fewest restrictions possible.

Machine Learning 52

Machine Learning ML Neural Network Auto-classification 52

The MLOps Blog

JUNE 27, 2023

Can you see the complete model lineage with data/models/experiments used downstream? Some of its features include a data labeling workforce, annotation workflows, active learning and auto-labeling, scalability and infrastructure, and so on. Is it accessible from your language/framework/infrastructure, framework, or infrastructure?

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Viso.ai

DECEMBER 22, 2023

Today, the computer vision project has gained enormous momentum in mobile applications, automated image annotation tools , and facial recognition and image classification applications. Convolutional Neural Networks (CNNs) CNNs are integral to the image encoder of the Segment Anything Model architecture.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Auto-classification 52

Mlearning.ai

MAY 23, 2023

Once the exploratory steps are completed, the cleansed data is subjected to various algorithms like predictive analysis, regression, text mining, recognition patterns, etc depending on the requirements. It is the discounting of those subjects that did not complete the trial. Classification is very important in machine learning.

Data Science 52

Data Science Neural Network Deep Learning Machine Learning 52

Explosion

JANUARY 31, 2021

The quickstart widget auto-generates a starter config for your specific use case and setup You can use the quickstart widget or the init config command to get started. When you load a config, spaCy checks if the settings are complete and if all values have the correct types. This lets you catch potential mistakes early.

NLP 52

NLP Python BERT Auto-classification 52

Dlabs.ai

JANUARY 16, 2023

The Mayo Clinic sponsored the Mayo Clinic – STRIP AI competition focused on image classification of stroke blood clot origin. Typical Neural Network architectures take relatively small images (for example, EfficientNetB0 224x224 pixels) as input. The neural network generated a [7, 7, 1280] -shape embedding for each tile.

Neural Network 52

Neural Network ML Auto-classification Convolutional Neural Networks 52

Mlearning.ai

JUNE 28, 2023

There will be a lot of tasks to complete. This is the link [8] to the article about this Zero-Shot Classification NLP. BART stands for Bidirectional and Auto-Regression, and is used in processing human languages that is related to sentences and text. Are you ready to explore? Let’s begin! The approach was proposed by Yin et al.

Machine Learning 52

Machine Learning NLP Auto-classification Natural Language Processing 52

John Snow Labs

JUNE 27, 2023

At their core, LLMs are built upon deep neural networks, enabling them to process vast amounts of text and learn complex patterns. The model’s ability to generate high-quality text has made it popular in various natural language processing (NLP) tasks such as text completion, question answering, and text generation.

Large Language Models 52

Large Language Models BERT Natural Language Processing NLP 52

The Stanford AI Lab Blog

MARCH 28, 2022

It is well known that grading is critical to student learning 2 , in part because it motivates students to complete their assignments. Figure 7 : Performance of different bug classification models with different RL agents. For example, variational auto-encoder started only with 32% precision, but it increased to 74.8%

Algorithm 52

Algorithm Auto-classification Automation Auto-complete 52

Jay Alammar

DECEMBER 16, 2020

This article focuses on auto-regressive models, but these methods are applicable to other architectures and tasks as well. The literature is most often concerned with this application for classification tasks, rather than natural language generation. A breakdown of this architecture is provided here. The model used here is DistilGPT2.

Explainability 52

Explainability Auto-classification Auto-complete Neural Network 52

Flipboard

APRIL 13, 2023

Recent advancements in ML (specifically the invention of the transformer-based neural network architecture) have led to the rise of models that contain billions of parameters or variables. To give a sense for the change in scale, the largest pre-trained model in 2019 was 330M parameters. We’ll initially have two Titan models.

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Generative AI ML AI AI 182

AWS Machine Learning Blog

JANUARY 31, 2024

If the image is completely unmodified, then all 8×8 squares should have similar error potentials. Prerequisites To follow along with this post, complete the following prerequisites: Have an AWS account. Depending on the size of dataset, running these cells could take time to complete. Each 8×8 square is compressed independently.

Computer Vision 118

Computer Vision Auto-complete Deep Learning Auto-classification 118

AWS Machine Learning Blog

NOVEMBER 30, 2023

Neural network torch: A neural network model that’s implemented using Pytorch. Neural network fast.ai: A neural network model that’s implemented using fast.ai. Deep learning algorithm: A multilayer perceptron (MLP) and feedforward artificial neural network. An AUPRC of 0.86

Machine Learning 118

Machine Learning Neural Network Algorithm Auto-classification 118