Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
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Updated
May 24, 2024 - Python
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Generalized and Efficient Blackbox Optimization System
DEEPScreen: Virtual Screening with Deep Convolutional Neural Networks Using Compound Images
An autoML framework & toolkit for machine learning on graphs.
A paper collection about automated graph learning
Nature-inspired algorithms for hyper-parameter tuning of Scikit-Learn models.
To utilize the Breast Cancer Wisconsin Dataset for machine learning purposes. The aim is to diagnose breast cancer by employing a supervised binary, distance-based classifier (K Nearest Neighbours), which will classify cases as either benign or malignant.
A gradient free optimization routine which combines Particle Swarm Optimization with a local optimization for each particle
Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
Pipoh is a library that implements several diversification techniques base on mean-variance framework. In addition, it includes a novel purely data-driven methods for determining the optimal value of the hyper-parameters associated with each investment strategy.
An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.
Python implementation that explores how different parameters impact a single hidden layer of a feed-forward neural network using gradient descent
Students Performance Evaluation using Feature Engineering, Feature Extraction, Manipulation of Data, Data Analysis, Data Visualization and at lat applying Classification Algorithms from Machine Learning to Separate Students with different grades
Students Performance Evaluation using Feature Engineering, Feature Extraction, Manipulation of Data, Data Analysis, Data Visualization and at lat applying Classification Algorithms from Machine Learning to Separate Students with different grades
Hyper-Parameter Optimisation experiment as part of my undergraduate dissertation (2019)
Grammaropt : a framework for optimizing over domain specific languages (DSLs)
Combined hyper-parameter optimization and feature selection for machine learning models using micro genetic algorithms
Pipelineopt, sckit-learn automatic pipeline optimization
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