-
### Idea Title
Stochastic Gradient Descent (SGD)
### Idea Description
Stochastic Gradient Descent updates the model's parameters by calculating the gradient of the loss function for a single train…
-
I would like to implement stochastic gradient descent from scratch @Anamaya1729
Thank you.
-
### Have you completed your first issue?
- [X] I have completed my first issue
### Guidelines
- [X] I have read the guidelines
- [x] I have the link to my latest merged PR
### Latest Merged PR Lin…
-
### Reason/inspiration (optional)
We would like a new entry on the `Stochastic Gradient Descent` concept under Sklearn. The entry should go in a new file under `docs/content/sklearn/concepts/stochast…
-
### Reason/inspiration (optional)
"We would like a new term entry in the `AI` concept for [neural-network](https://www.codecademy.com/resources/docs/ai/neural-networks): stochastic gradient descen…
-
I would like to suggest adding Optimization functions, machine learning and deep learning algorithms in this repository. This can be added in a separate folder called `machine_learning` folder. Furthe…
-
### Is there an existing issue for this?
- [X] I have searched the existing issues
### Feature Description
The work I propose involves:
Implementing key optimizers such as Stochastic Gradient De…
-
#### Description
Edit SGD to shuffle data before each inner loop
#### Files
* `touvlo/utils.py`
+ Location of SGD implementation
* `tests/test_utils.py`
+ Location of test cases fo…
-
To implement stochastic gradient descent to optimize a linear regression algorithm on Boston House Prices dataset which is already exists in sklearn as a sklearn.linear_model.SGDRegressor.here,SGD alg…
-
In the pdf it looks like the "Mini batch Stochastic Gradient Descent" explanation is repeated from SGD.
sri9s updated
5 years ago