GitHub / Heba-Atef99 / ML_optimization_algorithms
This is an implementation of different optimization algorithms such as: - Gradient Descent (stochastic - mini-batch - batch) - Momentum - NAG - Adagrad - RMS-prop - BFGS - Adam Also, most of them are implemented in vectorized form for multi-variate problems
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Language: Jupyter Notebook
Size: 7.34 MB
Dependencies parsed at: Pending
Created at: about 2 years ago
Updated at: about 2 years ago
Pushed at: about 2 years ago
Last synced at: about 2 years ago
Topics: adagrad, adam-optimizer, batch, bfgs-algorithm, gradient-descent, mini-batch, momentum-optimization-algorithm, multivariate, nag, rmsprop, stochastic