unite10h
Reinforcement Learning Meets Chain-of-Thought: Transforming LLMs into Autonomous Reasoning Agents
Large Language Models (LLMs) have significantly advanced natural language processing (NLP), excelling at text generation, translation, and summarization tasks. However, their ability to engage in ...
IEEE16d
An Efficient and Hybrid Deep Learning-Driven Model to Enhance Security and Performance of Healthcare Internet of Things
We provide a novel Software-Defined Networking (SDN)- driven Deep Learning (DL) approach to develop a secure ... Third, the past medical records of the patients are used to train the DL model. It then ...
Microsoft16d
Geospatial Machine Learning
including tabular learning with LightGBM and deep learning using Sequence-to-One models. Prerequisites include basic machine learning knowledge, Python programming skills, familiarity with deep ...
Frontiers18d
A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species
These range from classical linear mixed models to complex non-linear machine learning approaches, such as Support Vector Regression, and modern deep ... Venn diagram shows the number of SNPs which ...
unite20d
10 Best Machine Learning Certifications (February 2025)
This course is focused on how machine learning can harness data — no matter how small — to train an AI model. Featuring 5 instructors this ... You'll eventually understand how tree-based methods and ...
techxplore29d
Neural networks model improves machine vision and object detection under low-light conditions
It is a machine vision tool that is used to estimate objects' positions ... "The use of neural networks in the model allows us to detect this type of marker in a more flexible way, solving the problem ...