Notes about LLaMA 2 model
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Updated
Aug 30, 2023 - Python
Notes about LLaMA 2 model
A collection of various gradient descent algorithms implemented in Python from scratch
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.
[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
Short description for quick search
SC-Adagrad, SC-RMSProp and RMSProp algorithms for training deep networks proposed in
Hopfield NN, Perceptron, MLP, Complex-valued MLP, SGD RMSProp, DRAW
Python library for neural networks.
Object recognition AI using deep learning
Library which can be used to build feed forward NN, Convolutional Nets, Linear Regression, and Logistic Regression Models.
Fully connected neural network for digit classification using MNIST data
An OOP Deep Neural Network using a similar syntax as Keras with many hyper-parameters, optimizers and activation functions available.
Implementing a neural network classifier for cifar-10
AI-Face-Mask-Detector
Classification of data using neural networks — with back propagation (multilayer perceptron) and with counter propagation
gradient descent optimization algorithms
Siamese Neural Network used for signature verification with three different datasets
Investigating the Behaviour of Deep Neural Networks for Classification
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