Hands-on machine learning course with Python covering supervised learning (SVM, regression), unsupervised learning (K-Means, IRIS dataset), and deep learning (CNNs) using scikit-learn and TensorFlow.

Inspired by these developments, we propose a novel hyperspectral image classification method that integrates CNN and Transformer architectures. The method first employs 3D and 2D convolution ...

Understanding machine learning (ML) algorithm from scratch is time consuming. Thus, many software and library packages such as Weka and Scikit-Learn have been introduced to help researchers run ...

Contribute to Omri-Matalon/Classification-Models-with-Keras-and-Scikit-Learn-MNIST-Handwritten-Digits development by creating an account on GitHub.

A significant limitation of k-NN classification is that all predictor variables must be strictly numeric. There are several tools and code libraries that you can use to create a k-NN classifier. The ...

Wrapping Up When using the scikit library for multi-class classification, the main alternative to the MLPClassifier neural network module is the scikit DecisionTree module. Decision trees are useful ...

Thus, it limits the further applications of CNNs in BCIs. In order to build a robust classification algorithm for a calibration-less BCI system, we propose an end-to-end model that transforms the EEG ...