Handwritten-Digits-Classification-Using-KNN-Multiclass Perceptron-SVM🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
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MNIST-CoreMLPredict handwritten digits with CoreML
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mnist-drawDraw and classify digits (0-9) in a browser using machine learning
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videoMultiGANEnd to End learning for Video Generation from Text
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amrOfficial adversarial mixup resynthesis repository
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MNISTHandwritten digit recognizer using a feed-forward neural network and the MNIST dataset of 70,000 human-labeled handwritten digits.
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Mutual labels: mnist-dataset
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MNIST-cnnConvolutional neural networks with Python 3
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babble-rnnbabble-rnn is a research project in the use of machine learning to generate new speech by modelling human speech audio, without any intermediate text or word representations. The idea is to learn to speak through imitation, much like a baby might.
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