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119 public repositories
matching this topic...
Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games
A tour of different optimization algorithms in PyTorch.
Notes about LLaMA 2 model
A collection of various gradient descent algorithms implemented in Python from scratch
From linear regression towards neural networks...
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.
Modified XGBoost implementation from scratch with Numpy using Adam and RSMProp optimizers.
[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
📈Implementing the ADAM optimizer from the ground up with PyTorch and comparing its performance on six 3-D objective functions (each progressively more difficult to optimize) against SGD, AdaGrad, and RMSProp.
A fast, interactive tool to visualize how different gradient descent algorithms (like vanilla gradient Descent, Momentum, RMSprop, Adam, etc.) navigate complex loss surfaces in real time.
Short description for quick search
SC-Adagrad, SC-RMSProp and RMSProp algorithms for training deep networks proposed in
A Siamese Neural Network is a class of neural network architectures that contain two or more identical subnetworks. ‘identical’ here means, they have the same configuration with the same parameters and weights.
Dropout vs. batch normalization: effect on accuracy, training and inference times - code for the paper
Hands on implementation of gradient descent based optimizers in raw python
Hopfield NN, Perceptron, MLP, Complex-valued MLP, SGD RMSProp, DRAW
Neural Networks and optimizers from scratch in NumPy, featuring newer optimizers such as DemonAdam or QHAdam.
A research project on enhancing gradient optimization methods
Object recognition AI using deep learning
Python library for neural networks.
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