Zeus Project

LOOKING FOR MAINTAINERS - PLEASE REACH OUT TO cneuralnets@gmail.com

Welcome to the Zeus Project! This repository is a collection of educational posts and associated projects related to various topics in machine learning and data science. We aim to provide clear theoretical explanations along with hands-on projects to solidify understanding.

We welcome contributions from the community! If you have a topic you'd like to write about, please follow the steps below.

How to Contribute

To contribute a new blog post and project, you'll need to add two files: one for the blog content and one for the project description.

Step 1: Fork and Clone the Repository

Start by forking the repository to your own GitHub account and then clone it to your local machine.

git clone https://github.com/<your-username>/thezeusproject.github.io
cd thezeusproject.github.io

Replace <your-username> with your GitHub username

Step 2: Create New Content Files

A complete contribution consists of a blog post, a corresponding project, and an HTML page to display them.

1. Create a blog post: Navigate to the content/blog directory. The easiest way to start is to copy an existing blog post file, for example linear-regression.md, and rename it to your new topic (e.g., your-topic-name.md).

2. Create a project file: Similarly, go to content/projects and create a corresponding markdown file for the project tasks (e.g., your-topic-name.md). You can also copy an existing file from this directory to use as a template.

3. Create an HTML page: Go to pages/blog-pages. Copy an existing HTML file (e.g., linear-regression.html) and rename it to match your topic (e.g., your-topic-name.html).

Step 3: Add Your Content

Now, open the files you've created and add your content.

Blog Post (content/blog/your-topic-name.md)

At the beginning of your blog post file, you need to include a frontmatter section. This is crucial for the website to correctly display your post.

Here is an example of what the frontmatter should look like:

<!-- filler line (always add this filler line or code wont work)-->
---
title: Your Blog Post Title
subtitle: A brief and engaging subtitle for your post.
author: your-github-username
---

![image](assets/images/your-awesome-image.png)

## Section 1: Introduction

Your amazing content starts here...

• title: The title of your blog post.
• subtitle: A short description that will appear under the title.
• author: Your name or username.
• Image: You can add a header image. All images used in your blog post or project must be uploaded to the /assets/images/ directory. Link to them as shown above (e.g., ![image](assets/images/your-awesome-image.png)).

After the frontmatter, you can write the full content of your blog post in Markdown.

Project File (content/projects/your-topic-name.md)

The project file should contain a list of tasks for a hands-on project related to your blog post. Use Markdown checklists to create the tasks.

Here is an example structure:

### Project: Your Project Title

- [ ] **Task 1: A description of the first task**
  - [ ] A sub-task if needed.
- [ ] **Task 2: Another task**

Step 4: Update the HTML file

Open the new HTML file you created (pages/blog-pages/your-topic-name.html) and make sure the title and the paths to the markdown files are correct.

• Update Title: Change the <title> tag to reflect your blog post's title.
• Update Content Paths: Locate the fetch calls in the JavaScript section at the bottom of the file. Update the paths to point to your new markdown files in content/blog and content/projects.

For example, if your topic is your-topic-name, the fetch calls should look like this:

// ...
Promise.all([
    fetch('../../content/blog/your-topic-name.md').then(res => res.text()),
    fetch('../../content/projects/your-topic-name.md').then(res => res.text())
])
//...

Step 5 : Manually update the /assets/curriculum.js file

Please update the file with your blog details under the const blogs.

Step 6: Submit a Pull Request

Once you have created your blog post and project files, commit the changes and push them to your fork.

git add .
git commit -m "feat: Add new blog on [Your Topic]"
git push origin main

Then, go to the original repository on GitHub and open a Pull Request. We will review your contribution and merge it if everything looks good.

Organizing Blogs into Groups

The Zeus Project organizes blog posts into thematic learning groups to provide structured learning paths. Each group represents a major topic area in machine learning and data science.

Current Learning Groups

We currently have six main learning groups:

1. Classical ML - Fundamental machine learning algorithms and concepts
2. Deep Learning - Neural networks and deep learning architectures
3. Natural Language Processing - Text processing and language understanding
4. Computer Vision - Image processing and visual AI
5. Reinforcement Learning - Decision-making and sequential learning
6. MLOps & Deployment - Production ML systems and deployment

How to Add a Blog to a Group

When contributing a new blog post, you should add it to the appropriate learning group to ensure it appears in the group's lesson list and contributes to the group's progress tracking.

Step 1: Identify the Appropriate Group

Choose the group that best matches your blog's topic:

• Classical ML: Linear/logistic regression, decision trees, SVMs, clustering, ensemble methods, performance metrics
• Deep Learning: Neural networks, backpropagation, CNNs, RNNs, optimizers, regularization
• NLP: Text preprocessing, embeddings, transformers, sentiment analysis, language models
• Computer Vision: Image processing, object detection, image classification, facial recognition
• Reinforcement Learning: Q-learning, policy gradients, multi-agent systems, game theory
• MLOps: Model deployment, monitoring, CI/CD, containerization, cloud platforms

Step 2: Update Group Configuration Files

You need to update both of these JavaScript files:

1. assets/js/groups.js - Main groups page configuration
2. assets/js/group-detail.js - Individual group page configuration

In both files, find the appropriate group object and add your blog's ID to the blogIds array:

{
  id: 'classical-ml',
  title: "Classical ML",
  // ... other properties
  blogIds: ['linear-regression', 'performance-metrics', 'your-new-blog-id'], // Add your blog ID here
  // ... other properties
}

Also add your blog's metadata to the blogMetadata array in both files:

const blogMetadata = [
  // ... existing blogs
  {
    id: 'your-new-blog-id',
    title: "Your Blog Title",
    subtitle: "Your blog subtitle",
    html: 'blog-pages/your-blog.html', // Use '../blog-pages/your-blog.html' in group-detail.js
    tags: ['relevant', 'tags', 'for', 'your', 'blog']
  }
];

Step 3: Create Group Page (if needed)

If you're adding to a group that doesn't have a dedicated page yet (NLP, Computer Vision, Reinforcement Learning, or MLOps), you'll need to create one:

1. Copy an existing group page from pages/groups/ (e.g., classical-ml.html)
2. Rename it to match the group ID (e.g., nlp.html)
3. Update the content to reflect the new group's title, description, and topics
4. Update the script tag at the bottom to use the correct data-group-id

Step 4: Verify Group Assignment

After adding your blog to a group:

1. Your blog should appear in the group's lesson list
2. The group's progress bar should reflect completion of your blog's projects
3. The group should show the correct lesson count
4. All progress calculations should display with 2 decimal places

Best Practices for Group Organization

• One primary group: Each blog should belong to one primary group to avoid confusion
• Relevant grouping: Choose the group that most closely matches your blog's core topic
• Consistent metadata: Ensure your blog's metadata is identical in both configuration files
• Path correctness: Use relative paths (blog-pages/) in groups.js and (../blog-pages/) in group-detail.js
• Tag consistency: Use relevant tags that help with content discovery and filtering

Progress Tracking

Groups track learning progress with 2-decimal precision:

• Progress is calculated as: (completed_blogs / total_blogs) * 100
• A blog is considered "completed" when its project tasks reach 100% completion
• Group progress updates automatically as users complete blog projects
• Progress displays with format like "66.67% completed" instead of rounded integers

License

This project is licensed under the MIT License. See the LICENSE file for details.

Thank you for contributing to the Zeus Project!