Review Classification using Active Learning
Frontiers | A Deep Active Learning Approach to the Automatic Classification of Volcano-Seismic Events
Master Keras for Deep Learning Projects - A Beginner's Guide
Using Active Learning to Improve your Machine Learning Models – CV-Tricks.com
cleanlab 2.3 adds support for Active Learning, Tensorflow/Keras models made sklearn-compatible, and highly scalable Label Error Detection
AI Starter-Everything you need to know about Keras to build your first deep learning model | by Pallawi | Medium
PyRelationAL: A Library for Active Learning Research and Development | Semantic Scholar
Active Learning Tensorflow Implementation | by Moklesur Rahman | Medium
GitHub - google/active-learning
Active Learning on MNIST — Saving on Labeling | by Andy Bosyi | Towards Data Science
Why you should be using active learning to build ML
Comprehensive introduction to active learning with Tensorflow and Keras - Show and Tell - TensorFlow Forum
Active Learning and Semi-supervised Learning turn your unlabeled… – Towards AI
Transfer Learning in Keras (Image Recognition) - MarkTechPost
Active Learning and Human Involvement in Machine Learning | by Darshan Deshpande | Analytics Vidhya | Medium
Active learning: deduplication example | by Roman Kazinnik | Medium
Ppt model & strategi pembelajaran active learning membaca keras keras
Sebastian Raschka on X: "Active learning is one of these things that I wish was easier to use in practice. Labeling data is always the annoying part, so if you have a
How to use unlabelled data to get more training data | by Tivadar Danka | Medium
Active Learning for classification models | SuperAnnotate
cleanlab 2.3 adds support for Active Learning, Tensorflow/Keras models made sklearn-compatible, and highly scalable Label Error Detection
Compare deep learning frameworks - IBM Developer
Battle of the Deep Learning frameworks — Part I: 2017, even more frameworks and interfaces | by Indra den Bakker | Towards Data Science
cleanlab 2.3 adds support for Active Learning, Tensorflow/Keras models made sklearn-compatible, and highly scalable Label Error Detection
