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Achievement: Pull SharkAchievement: YOLO

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ronakrajput8882/README.md

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🎓 Final-year CE @ MBIT, CVM University · 📍 Anand, Gujarat
🔬 ML Intern @ CodeAlpha | AI/ML Intern @ MindInventory
🚀 Building LLM apps, RAG systems & ML pipelines that actually work

🛠️ Stack

Python PyTorch TensorFlow scikit-learn LangChain HuggingFace Pandas NumPy SQL Linux Git

🚀 Projects

🏠 House Price Prediction 👥 Employee Turnover Prediction
Linear Regression · R² 0.374 · MAE ~$30,829 Logistic Regression · L1/L2 · 16-feature HR dataset
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📊 GitHub Stats

GitHub Streak

Open to full-time AI/ML & Data Science roles — let's build something meaningful 🚀

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  1. SmartCart-Customer-Segmentation SmartCart-Customer-Segmentation Public

    🛒 An interactive Streamlit dashboard for retail customer segmentation using K-Means & Agglomerative Clustering with PCA — featuring EDA, 3D cluster visualization, segment profiling, and auto-genera…

    Python

  2. Shop-Smart-Ecommerce Shop-Smart-Ecommerce Public

    Built a binary classifier to predict whether an online shopping session ends in a purchase. The dataset has 12,329 sessions from a real e-commerce platform — with 17 behavioral features like page v…

    Jupyter Notebook

  3. CNN-Image-Classifier CNN-Image-Classifier Public

    CNN CIFAR-10 Image Classifier 🖼️ — Custom PyTorch CNN (75.1% acc) served via FastAPI with a fully custom UI. Deployed with Docker on HuggingFace Spaces. No Gradio, no Streamlit — built from scratch.

    HTML

  4. CodeAlpha-Emotion-Recognition-from-Speech CodeAlpha-Emotion-Recognition-from-Speech Public

    Speech Emotion Recognition using CNN-LSTM hybrid on RAVDESS dataset — 79.5% accuracy across 8 emotions.

    Python

  5. NovaGen-Health-Classifier NovaGen-Health-Classifier Public

    🧬 Binary health risk classifier for biomedical research | Random Forest (95.88% Recall) | sklearn · 9,800 records · 5 models compared

    Jupyter Notebook

  6. XGBoost-Classifier XGBoost-Classifier Public

    Most people test XGBoost on 10K rows. I wanted to see how it holds up at scale — 1,000,000 samples, 30 features, balanced binary classification. No tricks, just a well-tuned gradient boosting pipel…

    Jupyter Notebook