Skillverse Excellence Rank Predictor offer on all projects with expert help, documentation and source code.
Project Description
This project implements a Fake News Detection using ML suitable for BE major or minor in Data Science. Classifier and web interface. The deliverable includes full source code, documentation, report, and PPT. Our experts guide you through design, implementation, and deployment so you can demonstrate and defend the project confidently.
Problem Statement
Students and institutions need a reliable, well-designed Fake News Detection using ML that meets academic standards and real-world relevance in Data Science. The solution must be implementable within the given timeline, documented for submission, and scalable for future enhancements.
Technology used
Click a technology to learn more and why industry uses it.
Software Requirements
- Python 3.8+
- Jupyter Notebook / VS Code
- Libraries: pandas, numpy, scikit-learn, matplotlib
- Optional: TensorFlow/PyTorch for deep learning
- Database: SQLite or MySQL if applicable
Hardware Requirements
- Processor: Intel i3 / AMD equivalent or better
- RAM: 4 GB minimum (8 GB recommended)
- Storage: 2 GB free space
- Display: 1366×768 or higher
Reviews
Helped me understand every module. Great for last-year project.
Smooth process from start to delivery. Documentation was thorough.
Exceeded expectations. On-time delivery and ready-to-run code.
Got my project delivered on time with full documentation. Defended successfully. Highly recommend.
Why choose us
Compare Skillverse Excellence with other options. We focus on quality, support, and value for students.
| Feature | Skillverse Excellence | Other agencies | ChatGPT / Vibe coding |
|---|---|---|---|
| Quick and online delivery | |||
| WhatsApp support for 15 days after delivery | |||
| Expert help with project | Limited | ||
| Expert-reviewed code | |||
| Less garbage code and focused output | |||
| Experts include IITians, NITians, alumni | Limited | ||
| Expert with 10+ years industry experience | Limited | ||
| Use of latest stack and tools | Limited | ||
| Always updated, maintainable code | |||
| Runs on Windows, Linux & macOS | |||
| Follows proper academic guidelines (report, PPT, format) | Limited | ||
| Step-by-step documentation with comments | |||
| Professionally designed Word/PPT | Limited | ||
| LaTeX template provided | |||
| 15-min Google Meet with expert | |||
| Minor changes during delivery window | |||
| Custom project ideas | |||
| One-click deployment / running code | |||
| 100% money-back guarantee (if not satisfied) | |||
| 100% satisfaction guarantee | |||
| Value per rupee spent | Limited | ||
| 30% discount on project (Limited time offer) | |||
| Outdated or legacy stack | |||
| Code that runs on only one platform | |||
| Ignores academic guidelines |
