A dynamic hub of Machine Learning innovations, where hands-on projects and collaborative experiments come together to inspire open-source contributions and foster a community of shared learning.
This repository is a diverse collection of projects ranging from beginner-friendly models to advanced AI applications. Whether you're new to the field or a seasoned expert, there's something for everyone to contribute to. Dive into neural networks, computer vision, natural language processing (NLP), and more. Join our vibrant community, share your ideas, and help shape the future of AI—together!
Join official Discord Channel for discussion
Natural Language Processing (NLP)
Projects in this area involve working with text data, such as sentiment analysis, language translation, text summarization, and chatbot development using techniques like tokenization, word embeddings, and transformers.
Computer Vision
Contributors can explore projects related to image classification, object detection, facial recognition, and image segmentation using tools like OpenCV, convolutional neural networks (CNNs), and transfer learning.
Neural Networks
Neural networks power most deep learning models. Contributions could include creating models for image classification, regression tasks, sequence prediction, and generative models using frameworks like TensorFlow or PyTorch.
Generative Models
This includes working on projects related to Generative Adversarial Networks (GANs) for image generation, text-to-image models, or style transfer, contributing to fields like art creation and synthetic data generation.
Time Series Analysis
Contributors can work on analyzing temporal data, building models for stock price prediction, climate forecasting, or IoT sensor data analysis using LSTM or GRU networks.
Transfer Learning
Explore projects where pre-trained models are fine-tuned for specific tasks, such as custom object detection or domain-specific text classification, reducing the need for extensive training data.
You can refer to the following articles on the basics of Git and Github.
- Watch this video to get started, if you have no clue about open source
- Forking a Repo
- Cloning a Repo
- How to create a Pull Request
- Getting started with Git and GitHub
- Take a look at the Existing Issues or create your own Issues!
- Wait for the Issue to be assigned to you.
- Fork the repository
click on the uppermost button
- Clone your forked copy of the project.
git clone --depth 1 https://github.com/<your_user_name>/ML-Nexus.git
## Installation 👇
```bash
pip install -r requirements.txt
- Have a look at Contributing Guidelines
- Read the Code of Conduct
Kalyani 👑 Admin |
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|---|---|
| Sai Nivedh V 🔧 Mentor |
Pratyay Banerjee 🔧 Mentor |
If you want to propose an idea, please create an issue and tag @UppuluriKalyani, @Neilblaze, and @SaiNivedh in the issue. Kindly wait until the issue is assigned to you before starting any work.
Assignments will be made on a first-come, first-served basis—whoever requests the issue first will be assigned. Please cooperate and help us improve our project!
After submitting a pull request, please give us time to review it. If everything looks good, we will merge it automatically. If any changes are needed, we’ll request them. Please be patient while we go through this process.
Please do! Contributions and pull requests are welcome.Contributors are expected to adhere to the Code of Conduct.
Jump into our Discord!
To maintain a safe and inclusive space for everyone to learn and grow, contributors are advised to follow the Code of Conduct.
If you have any feedback or suggestions please reach out to Project - Maintainer.
Or you can create a issue and mention there , which new features or extension can make this Project more good.