Suggestion: Add optimization functions, ml algorithms under `machine_learning` folder
Navaneeth-Sharma opened this issue · 11 comments
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. Further, this folder can contain various algorithms that are used in machine learning and deep learning.
Initially, these Optimization functions can be added under machine_learning/optimization/
- Gradient Descent
- Stochastic Gradient Descent (SGD)
- Mini-Batch Gradient Descent
- Adam (Adaptive Moment Estimation)
- RMSprop (Root Mean Square Propagation)
- AdaGrad (Adaptive Gradient Algorithm)
And these in machine_learning/
- Linear Regression
- Logistic Regression
- Decision Trees
- Random Forest
- Support Vector Machines (SVM)
- K-Nearest Neighbors (K-NN)
- Naive Bayes
- K-Means Clustering
- Principal Component Analysis (PCA)
I like the idea, let's do that
@Navaneeth-Sharma @siriak Lets also keep loss functions in that folder. #582
This issue has been automatically marked as abandoned because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
@siriak hey, can you do something, so that it doesn't get automatically close. I think it should remain open.
Hello I am new to open source contribution, I would love to help in implementing some of the optimisation techniques. Kindly let me know if someone is already working on them, or I can start working with few?
Pull request has been raised for K-Nearest Neighbors Algorithm (#723). Request you to please check on that
Hello, I would love to start contributing to this project. Specifically on optimization algorithms like Stochastic Gradient Descent (SGD) or Mini-Batch Gradient Descent. Are they still possible to work on them?
Sure, you can start implementing them