kyegomez/gradient-ascent
A new optimizer, Gradient Ascent: Gradient Ascent adjusts the parameters in the direction of the gradient to maximize some objective function.
This tool helps machine learning engineers and researchers optimize models by maximizing an objective function. You provide the model and the function you want to maximize, and it intelligently adjusts the model's internal settings to achieve the best possible outcome. This is especially useful for tasks where you're trying to achieve a peak performance or a highest likelihood.
No commits in the last 6 months. Available on PyPI.
Use this if you are building machine learning models for tasks like maximizing data likelihood, training generative models (like GANs), or optimizing policies in reinforcement learning.
Not ideal if your primary goal is to minimize a loss function, which is the more common scenario for most machine learning training.
Stars
10
Forks
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Language
Python
License
MIT
Category
Last pushed
Mar 11, 2024
Commits (30d)
0
Dependencies
2
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