The Tech Edvocate

How to use Keras

Spread the love“`html Keras has emerged as one of the most popular deep learning libraries in recent years, notable for its simplicity and ease of use. Whether you’re a seasoned data scientist or a ...

IIT Roorkee Opens Admissions for the 11th Batch of its Post Graduate Certificate in Data Science, Machine Learning & Generative AI

Eight-month live online programme by CEC, IIT Roorkee equips professionals to build applied expertise across Python, machine learning, deep learning, MLOps, LLMs and Generative AI, Education, Times No ...

How Machine Learning Is Quietly Reshaping One of International Trade's Oldest Bottlenecks

LOS ANGELES, CA / ACCESS Newswire / June 11, 2026 / For most consumers, the journey of a package across international borders feels invisible. A box leaves a warehouse, crosses an ocean, and arrives ...
AZoNano

Machine Learning Reveals Hidden Nanophotonic Resonances In Silicon-Gold Nanopillars

Researchers developed a hybrid UMAP-HDBSCAN-SVM machine learning workflow to rapidly classify low-loss STEM-EELS spectrum ...

Classiq and UC Chile Launch Quantum AI Research for Biomedical Image Analysis Leveraging Integration with NVIDIA CUDA-Q

The 12-month engagement, titled “Enhancing Pathology through Quantum Computing,” is funded through Avanza UC 2025, the Internal Research and Creation Competition of UC Chile. To the collaborators’ ...
IEEE

Comparing Automated Machine Learning Against an Off-the-Shelf Pattern-Based Classifier in a Class Imbalance Problem: Predicting University Dropout

Abstract: When facing a classification problem, data science practitioners must search through an armory of methods. Often, practitioners are tempted to use off-the-shelf classifiers, including ...
holisticai

Bias Mitigation Strategies and Techniques for Classification Tasks

The bias problem in classification tasks and the different strategies used for bias mitigation. How these strategies are grouped into categories and a brief introduction of the most representative ...
C&EN

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.
LinkedIn

Artificial Neural Network Model Classification and Regression

Unlike human beings who often learn for the intrinsic value of knowing something, machine-learning is almost always purpose-driven. Your job as the machine's developer is to determine what that ...
LinkedIn

Converting Regression Problems into Classification Problems in Machine Learning: A Learner's Guide

Machine learning encompasses a variety of techniques tailored to solve different types of problems. Two primary categories of supervised learning are regression and classification. Regression focuses ...
Nature

Boosting ridge for the extreme learning machine globally optimised for classification and regression problems

This paper explores the boosting ridge (BR) framework in the extreme learning machine (ELM) community and presents a novel model that trains the base learners as a global ensemble. In the context of ...