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Metaheuristic-Binary-Optimizer-for-Feature-Selection---BPSO
The binary version of this meta-heuristic optimizer is used for feature selection process through a wrapper based method. The Optimizer is set with a threshold value, provided they consider the random subset of data over each iteration and train the system and finally land up with minimum feature subset with best classification accuracyMetaheuristic-Optimizer-for-Feature-Selection---PSO
The following gives information regarding the Particle Swarm Optimizer for feature selection process using various machine learning classifiers within the classification functionSemantic-Search-Engine
Implementation-and-Optimizations-using-KNN-Machine-Learning-Algorithms
Implementation of machine learning algorithms for the evaluation of data from the wearable sensors such as FSR, EMG and Strain Gauge which are used for the classification purpose of various sign recognitionsProjects
The folder contains the list of projects worked on Machine Learning, Deep Learning, Natural Language Processing, Computer Vision and other Libraries like scikit learn, tensorflow, keras, numpy, pandas, matplotlib, pillow, openCV, etc.Signal-Conditioning-Arduino
Master Control CircuitMachine-Learning-Engineer-Udacity
MERIDA
LeetCode
Summarizers
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