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Content for onestep-electron.github.io

Home Page: https://onestep-electron.github.io

License: MIT License

Jupyter Notebook 100.00%

machine-learning knn kmeans decision-trees random-forest svm linear-regression logistic-regression hacktoberfest hacktoberfest-2022 hacktoberfest-accepted

onestep-electron-content's Introduction

Click here to view the live website.

OneStepML - Content Repository

Welcome to OneStepML.

"The one-step, open-source destination for all things ML."
"A FREE platform for student developers, made by the student developers..."

OneStepML is a community-led, open-sourced, e-learning platform for Machine Learning and Data Science, developed with ❤️ at elecTRON.

OneStep Server Repo : Here

OneStep Client Repo : Here

🧐 Why OneStep-elecTRON?

Absolutely FREE: Yes. OneStepML is a non-profit organization with one aim— to put an end to the culture of putting education behind paywalls!
Machine Learning Tracks: Learn machine learning from basics to advanced, with hand-crafted and trusted content.
Python Learning Tracks: New to machine learning? Start by getting familiar with Python first with our Python Crash Course!
No Sign-In Required: Students can learn without logging in too! We do not share/sell your data. You only need to register (optional) to keep track of your progress and the quizes you have solved.
Live Code Execution: Execute you Python code right away inside an integrated code editor. You don't need powerful PCs to learn ML!
Interactive Quizzes: Track your learning with interactive quizzes, and get your answers right away.
Run on Colab Integration: Practice and learn via hands-on exercises/tutorials in Google Colab Notebooks.

The website is live here.

🔴 Be Part of Our Community

Join our Discord and be part of OneStep community. Feel free to interact with other community members and also get your doubts cleared regarding anything OneStep related.
Link to the server - https://discord.com/invite/cwxfhByeBf

👾 Build

This is the content repository for OneStepML, where you can contribute towards the development of the educational content for OneStepML. Please read our Contribution Guide before submitting a Pull Request to the project.

onestep-electron-content's People

Contributors

Stargazers

Forkers

satorugojo3795 sudharsansrini hemanthsai7 debjitl45

onestep-electron-content's Issues

Content Request: Introduction to Artificial Neural Networks

An article on ANNs and how they work, along with the mathematics associated with it, can come under the Intermediate track.
Additionally, you can also add a started notebook in PyTorch or Tensorflow for using ANNs for classification/regression.

NOTE: Make sure that the content is not plagiarized.

Documentation request

I would like to improve and add a new documentation for this repository

Content Enhancement : Logistic Regression

We are looking forward to improve the content of Logistic Regression and we wish to add the below mentioned changes -

Theory - The explanation right now is good but we would like to have something that's easier for the people to understand and grasp.
Math - We need to include a solved example to demonstrate the mathematical intuition of Logistic regression.

Found a typo in SVM.md

Hello there, I found a small typo in SVM.md thought of fixing it. I have gone through Contributing Guidelines.
Here's a snapshot of the typo I found.

I think it must be 'SVM are used mostly for classification type problems'.
I would like to fix this issue.

Content Suggestion for Intermediate Track

We are planning to expand the platform further and trying to bring in more quality content for the page. Suggestions regarding what should be added to the Intermediate Track are welcome under this issue. We will further select and assign the respective issues to the people based on their suggestions.

Implement a GitHub action for automating plagiarism check.

Each time a PR is made for a new content article, right now we have to manually perform a plagiarism check on the articles. Create a GitHub action workflow for automating this process. You can use some of the open-source/free plagiarism detection websites on the internet for the same.

Content Enhancement : KNN

The below mentioned additions are required -

Math - We need to add a solved example to show the working of the algorithm. To be precise, a pen and paper example of the math behind the algorithm with help of images like we have used for other algorithms.

Content Enhancement : Linear Regression

The theory part for the Linear regression in Easy track is not up to the mark from the feedbacks that we have received. Hence, we are trying to upgrade it and make it better. Additions that we are planning to make -

Theory - Content that's easy to understand and hits on the important and core topics of Linear Regression.
Math - Inclusion of the complete math of Linear Regression along with examples.

Content Suggestion for Advanced Track

With improvements being made in all the tracks, we are also looking forward to expand the Advanced track and are open to take in your suggestions. Before posting your suggestions, make sure that you have visited the website at least once and are aware of the pre existing content on the page.