A collaborative design and development project — working alongside Pranav Kumar to craft a premium, performance-optimized portfolio that powerfully communicates his expertise in Machine Learning, Deep Learning, and Data Science.
Pranav Kumar is an aspiring Data Scientist graduating from Galgotias University with hands-on experience in ML and DL. He needed a portfolio that could stand out in a competitive field — one that doesn't just list projects, but tells a data-driven story. I collaborated with him to design and build exactly that.
Pranav approached me with a clear goal — he needed a portfolio that showcased his AI/ML projects with credibility and impact, appropriate for job applications and IEEE-level academic recognition.
I contributed as the design and development partner — leading the visual direction, UX architecture, and front-end build. Pranav provided all the technical content, project data, and domain expertise on the data science side.
A fully deployed, responsive data science portfolio hosted on Vercel — featuring 6 ML projects with accuracy benchmarks, an IEEE publication, hackathon achievements, and a clean contact experience.
Turning raw ML expertise into a compelling digital presence.
A clean, data-centric visual system built for credibility and clarity.
Inter was chosen for its exceptional legibility at small sizes — critical for rendering data metrics and accuracy scores. Space Grotesk adds character to headings, giving the portfolio a distinctive, modern tech feel.
A high-contrast dark theme with cyan accents — chosen to evoke data streams, neural networks, and the precision of machine learning systems.
Each project was carefully presented with accuracy benchmarks, tech stacks, and visual context to maximize credibility and impact.
VGG16 transfer learning model with Grad-CAM visualization for interpretability. Achieved 97.75% accuracy.
TF-IDF vectorization + Multinomial Naive Bayes NLP pipeline for SMS/email classification. Achieved 97.80% accuracy.
CNN built with TensorFlow & Keras trained on 32,461 images with data augmentation. Achieved 97.00% accuracy.
Competitive hackathon achievement showcased prominently to demonstrate real-world problem-solving under pressure.
Published IEEE research paper featured as a key credibility marker — using XGBoost, Random Forest, and SVM for malignant vs benign tumour prediction.
Collaborating with Pranav on his portfolio was a rewarding experience in cross-disciplinary teamwork — his deep domain expertise in data science combined with my design and frontend skills resulted in a product that neither of us could have built alone.
The final portfolio is more than a website — it's a strategic tool that positions Pranav as a credible, high-achieving Data Scientist ready for industry. From the accuracy benchmarks to the IEEE publication badge, every design decision was intentional and data-backed. Visit it live at pranav-portfolio-two-ruddy.vercel.app .
Connect with Pranav Kumar