The MLOps Blog

FEBRUARY 22, 2024

TL;DR: In many machine-learning projects, the model has to frequently be retrained to adapt to changing data or to personalize it. Continual learning is a set of approaches to train machine learning models incrementally, using data samples only once as they arrive. What is continual learning?

Continuous Learning 59

Continuous Learning Machine Learning ML Neural Network 59

Unite.AI

DECEMBER 19, 2023

This is done on the features that security vendors might sign, starting from hardcoded strings, IP/domain names of C&C servers, registry keys, file paths, metadata, or even mutexes, certificates, offsets, as well as file extensions that are correlated to the encrypted files by ransomware.

Neural Network 147

Neural Network Deep Learning ML Metadata 147

Pickl AI

AUGUST 28, 2023

Various ranking algorithms, such as TF-IDF (Term Frequency-Inverse Document Frequency) and BM25, are used to determine the order in which documents are presented to the user. User Interaction and Feedback: Some IR systems learn from user interactions to improve their performance over time.

NLP 52

NLP Natural Language Processing Algorithm Data Mining 52

Heartbeat

JULY 5, 2023

Train the chatbot: Train the chatbot using reinforcement learning algorithms. The chatbot should also be trained to learn from its mistakes and adjust its behavior accordingly. Monitor its performance and continue to refine its behavior based on user feedback.

NLP 52

NLP Chatbots Natural Language Processing Deep Learning 52

Pickl AI

JANUARY 16, 2024

Continuous Learning Commitment to staying updated on industry trends and emerging technologies. Predictive Modeler Harnessing the power of algorithms to forecast future trends, aiding businesses in strategic decision-making. billion 15.83% Metadata-Driven Data Fabric Systematic data management efficiency. billion 26.4%

Data Analysis 52

Data Analysis Data Scientist Data Science Machine Learning 52

Sebastian Ruder

FEBRUARY 23, 2023

d) Hypernetwork: A small separate neural network generates modular parameters conditioned on metadata.  Instead of learning module parameters directly, they can be generated using an auxiliary model (a hypernetwork) conditioned on additional information and metadata. Soft learned routing.  Soft Fixed routing.  Fixed

Deep Learning 52

Deep Learning NLP Computer Vision Metadata 52

AWS Machine Learning Blog

SEPTEMBER 28, 2023

As it fields more queries, the system continuously improves its language processing through machine learning (ML) algorithms. Metadata about the request/response pairings are logged to Amazon CloudWatch. The CloudWatch log group is configured with a subscription filter that sends logs into Amazon OpenSearch Service.

Generative AI 96

Generative AI Artificial Intelligence Artificial Intelligence Large Language Models 96