Classiq 1.0 is designed for enterprise quantum R&D groups, algorithm developers, researchers and engineering teams that need to connect classical logic and constraints to quantum models and carry that ...
Hybrid Quantum-Classical Algorithm for an Integrated Feature Selection and Logistic Regression Model
Abstract: Feature selection is a pivotal step in machine learning, aimed at reducing feature dimensionality and improving model performance. Conventional feature selection methods, typically framed as ...
Quantum computing technology is complex, getting off the ground and maturing. There is promise of things to come. potentially changing the computing paradigm.
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Overview Quantum computing skills now influence hiring decisions across technology, finance, research, and national security sectors.Employers prefer cand ...
🚀 An end-to-end quantitative portfolio optimization & stock intelligence tool built with Python & Streamlit. Analyze NSE, BSE & NYSE stocks with predictions, portfolio optimization, risk metrics, and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results