On the Variance of the Adaptive Learning Rate and Beyond
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adam-optimizer
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Deep learning library in plain Numpy.
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This repository contains the results for the paper: "Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers"
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A book on the mathematical foundations of AI from an engineering perspective.
machine-learning books ai deep-learning calculus neural-network knowledge book optimization matrix linear-regression linear-algebra mathematics ml artificial-intelligence convergence educational derivatives integrals adam-optimizer
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CS F425 Deep Learning course at BITS Pilani (Goa Campus)
machine-learning deep-neural-networks deep-learning generative-model optimisation bits-pilani adam-optimizer
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ADAS is short for Adaptive Step Size, it's an optimizer that unlike other optimizers that just normalize the derivative, it fine-tunes the step size, truly making step size scheduling obsolete, achieving state-of-the-art training performance
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Lion and Adam optimization comparison
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Google Street View House Number(SVHN) Dataset, and classifying them through CNN
machine-learning computer-vision cnn dropout mnist svhn convolutional-neural-networks confusion-matrix google-street convolutional-neural-network tensorboard-visualizations tesnorflow svhn-classifier grayscale-images house-numbers adam-optimizer mini-batch-gradient-descent one-hot-encode
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Reproducing the paper "PADAM: Closing The Generalization Gap of Adaptive Gradient Methods In Training Deep Neural Networks" for the ICLR 2019 Reproducibility Challenge
tensorflow optimization keras wide-residual-networks adam-optimizer tensorflow-eager amsgrad sgd-momentum padam
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PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"
machine-learning computer-vision deep-learning neural-network solutions tensorflow numpy jupyter-notebook stanford-university assignment pytorch recurrent-neural-networks lstm generative-adversarial-network style-transfer convolutional-neural-networks backpropagation svm-classifier adam-optimizer sgd-optimizer
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Toy implementations of some popular ML optimizers using Python/JAX
machine-learning momentum gradient-descent optimization-algorithms adam adam-optimizer jax optimizers
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A collection of various gradient descent algorithms implemented in Python from scratch
machine-learning ai deep-learning machine-learning-algorithms ml deep-learning-algorithms gradient-descent adagrad rmsprop gradient-descent-algorithm adam-optimizer nesterov-accelerated-sgd nesterov-momentum nesterov momentum-optimization-algorithm
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This library provides a set of functionalities for different type of deep learning (and ML) algorithms in C
c library deep-learning neural-network opencl transformer lstm convolutional-layers deeplearning residual-layers residual-networks backpropagation optimization-algorithms softmax adam-optimizer avarage nesterov adam-algorithm dropout-layers
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From linear regression towards neural networks...
data-science machine-learning neural-network linear-regression machine-learning-algorithms data-analysis logistic-regression gradient-descent backpropagation adagrad rmsprop generalized-linear-models multilayer-perceptron-network adam-optimizer nesterov-accelerated-sgd nesterov-momentum nadam
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Modified XGBoost implementation from scratch with Numpy using Adam and RSMProp optimizers.
numpy gradient-boosting-machine rmsprop adam-optimizer xgboost-algorithm implementation-of-algorithms
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The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.
deep-neural-networks deep-learning time-series recurrent-neural-networks pca-analysis rnn adagrad rmsprop leaky-relu adam-optimizer random-forest-regressor adamax
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Lookahead optimizer ("Lookahead Optimizer: k steps forward, 1 step back") for tensorflow
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A compressed adaptive optimizer for training large-scale deep learning models using PyTorch
hashing deep-learning neural-network pytorch transformer imagenet count-min-sketch language-model adagrad adam-optimizer sgd-optimizer count-sketch sgd-momentum
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[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
adadelta momentum gradient-descent optimization-methods optimization-algorithms adam adagrad rmsprop gradient-descent-algorithm stochastic-optimizers stochastic-gradient-descent gradient-boosting adam-optimizer adamax stochastic-optimization batch-gradient-descent nesterov-accelerated-sgd amsgrad nesterov-momentum nadam
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