Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...
IPWatchdog

SCOTUS Scraps Recentive’s Petition Seeking Clarity on Eligibility for Machine Learning Claims

The U.S. Supreme Court today declined to grant a petition filed by Recentive Analytics, Inc. asking the Court to weigh in on ...
Que.com on MSN

Understanding AI: Breaking down machine learning, deep learning, and generative AI

Artificial Intelligence (AI) has become a buzzword in today’s tech-driven world, promising new possibilities and reshaping industries. Despite its prevalence, ...

It took me 2.5 years to transition to an AI team at Google. These 11 books to help me pivot.

Rahul Kasanagottu is an engineer at Google who pivoted to an AI role at the company after a 2.5 year upskilling journey.
Tech Xplore

Overparameterized neural networks: Feature learning precedes overfitting, research finds

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...
IEEE

Prompt-Based Concept Learning for Few-Shot Class-Incremental Learning

Abstract: Few-Shot Class-Incremental Learning (FSCIL) faces a huge stability-plasticity challenge due to continuously learning knowledge from new classes with a small number of training samples ...
istockphoto

Artificial Intelligence or machine learning vector design. Quantum computer technology concept with circuit board and motherboard texture background design. Waves flow quantum ...

Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...
Scientific Research Publishing

Yang, Q., Liu, Y., Chen, T. and Tong, Y. (2019) Federated Machine Learning: Concept and Applications. ACM Transactions on Intelligent Systems and Technology, 10, 1-19.

ABSTRACT: This paper presents a comprehensive machine learning approach for credit score classification, addressing key challenges in financial risk assessment. We propose an optimized CatBoost-based ...