ECUBE ANALYTICS - Data Science And Machine Learning Business Consultancy And Education In Surat

Skin cancer Detection and classification using computer vision

(Computer Vision)
End-to-end pipeline for skin-lesion classification on the ISIC 2018 dermoscopy dataset. Compares a custom CNN against EfficientNet-B3 transfer learning, for both 7-class diagnosis and binary malignant/benign, with Grad-CAM explainability. PyTorch; deployed on Hugging Face. VIEW PROJECT

BedOps AI — Hospital Length-of-Stay Predictor

(MLOps (SageMaker + Cloud Run))
Predicts a hospital patient's Length-of-Stay category (4 bands) at admission, so ward managers can plan bed allocation and discharge ahead of time. Optuna-tuned LightGBM on 318k records, served from a live Amazon SageMaker Serverless Inference endpoint behind a Cloud Run UI. VIEW PROJECT

Stroke-Prediction

(Machine Larning: Classification)
Predicts stroke risk from routine clinical and lifestyle inputs (age, hypertension, heart disease, glucose, BMI, smoking status) to flag at-risk patients early. Around 95% precision, recall and F1 with 0.99 ROC-AUC on the source study's data. Streamlit app. VIEW PROJECT

DIABETES PREDICTION STREAMLIT APP

(Machine Learning: Classification)
Proof-of-concept tool that estimates the probability of diabetes from easily measured clinical features. Trained on a real but older, single-ethnicity dataset, so it is used for teaching and client demonstrations rather than diagnosis. Streamlit app. VIEW PROJECT

Predicting Probability Of Heart Attack

(Machine Learning: Classification)
Self-check heart-attack risk estimator from routine inputs (age, blood pressure, cholesterol, glucose, BMI, smoking). XGBoost (5-fold CV, grid search) with a custom probability cutoff, F1 96.7%, plus a per-patient breakdown of which factors move the risk. On Hugging Face. VIEW PROJECT

SPAM_HAM-CLASSIFIER: E2E PROJECT WITH MODEL MONITORING AND MODEL DRIFT ANALYSIS

(Machine Learning: Classification)
Email spam/ham detector built as a full MLOps pipeline: tuned for precision, F1 and AUCPR on imbalanced data, with scheduled drift detection and automated retraining (MLflow, Airflow, Evidently). Streamlit + FastAPI, deployed on Cloud Run. VIEW PROJECT

Marketing Campaign Success Prediction

(End To End Machine Learning Projects)
Predicts whether a digital ad campaign will hit its conversion target, reframed as binary classification over budget, impressions, CTR, ad type and audience segment. XGBoost, ~91% test accuracy, custom UI. Deployed end-to-end on Google Cloud Run. VIEW PROJECT

Recommender System for Campaign CTR Prediction

(End To End Machine Learning Project)
End-to-end pipeline that predicts marketing-campaign click-through rate, reading training data from BigQuery and combining XGBoost regression with a hybrid recommendation approach. MLflow tracking, Docker, Cloud Build. Deployed on Google Cloud Run. VIEW PROJECT

Risk and Sentiment Intelligence Engine for Stock-Analyst Ratings Using PySpark and Azure Cognitive Services

(NLP+Azure Cognitive Services)
Text-analytics pipeline for analyst commentary: classifies sentiment, flags risky financial signals, and extracts company and instrument names. PySpark, scikit-learn/XGBoost, Azure Language API for NER, FastAPI. Deployed on Azure Container Apps. VIEW PROJECT

PROPERTY PRICE PREDICTION FOR INDIAN METRO CITIES (REAL DATA)

(End To End Machine Learning Regression)

Predicts residential property prices across six Indian metros (Mumbai, Delhi, Kolkata, Chennai, Hyderabad, Bengaluru) from real 2022 data. A separate grid-search-tuned XGBoost model per city, with locality as a feature. Multi-page Flask app on Google Cloud Run.

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A SUPERPOWERFUL GENERIC CLASSIFER (BINARY OR MULTICLASS)

(Machine Learning: Classification)
Upload any CSV or XLSX and build a classifier without writing code: automated EDA, 13 algorithms to choose from, slider-tuned hyperparameters, full evaluation reports, and seven diagnostic plots each with a short how-to-read note. 86 tests. Streamlit app. VIEW PROJECT

Multiagent Stock Market Technical And Fundamental Analysis

(Agentic AI)
A multi-agent system that answers natural-language stock questions using deterministic fundamental and technical analysis. Missing tickers are fetched on demand and cached as structured micro-indexes. Python 3.11, Alpha Vantage, RSI/SMA/EMA rules, Gradio UI. VIEW PROJECT

LSTM-Based Stock Price Predictor

(Neural Networks)
LSTM time-series forecaster with an interactive Streamlit UI. Epochs, window size, batch size and dropout are slider-controlled, training and validation loss plot live, and a pretrained model loads on launch for an instant demo. TensorFlow/Keras; W&B tracking; on Hugging Face. VIEW PROJECT

VAR(Vector Autoregression)-Based Forecasting of Bitcoin, Gold, and S&P 500

(TIme_Series Forecasting)
Multivariate VAR forecaster for Bitcoin, gold and the S&P 500. Lag order is chosen by ADF stationarity tests and an AIC grid search; the horizon is selectable from 4 to 12 weeks, with exportable forecast plots and tables. statsmodels, Gradio UI, on Hugging Face. VIEW PROJECT

Loan Eligibility Prediction Chatbot

(Machine Larning: Classification)
Conversational loan-eligibility screener built on real US lending data. Users enter a profile and get an instant approve / not-approved decision plus the factors driving it. Lightweight random-forest model for real-time response. Streamlit app. VIEW PROJECT

Customer Churn (Banking) With SHAP Analysis

(Machine Learning: Classification)
Predicts which retail-banking customers are likely to churn, using a reproducible pipeline on real 10,000-customer data. XGBoost with SHAP explanations at both the segment and individual-customer level. Flask app with an interpretable, plot-driven UI. VIEW PROJECT

OCR + NER Legal Document Extraction App

(Computer Vision)
Extracts named entities from scanned .tif and .pdf legal documents. Runs fully offline (no cloud APIs) using Tesseract/PaddleOCR for OCR and spaCy, BERT, Legal-BERT and regex for NER. Outputs JSON or CSV with confidence scores. Gradio UI. VIEW PROJECT

Vision Transformer Based Gradio App For Empty Parking Lot Detection

(Computer Vision)
Detects whether a parking space is occupied using a Vision Transformer trained on the PKLot benchmark dataset. The transformer architecture outperformed convolutional baselines on this image-classification task. Gradio prototype of a smart-parking solution. VIEW PROJECT

PRECISION FARMING (SMART AGRICULTURE)

(Machine Learning: Classification)
Crop-recommendation tool that suggests the best crop to plant from seven soil and climate inputs: nitrogen, phosphorus, potassium, temperature, humidity, pH and rainfall. Multi-class Naive Bayes model. Streamlit app; second prize at a hackathon. VIEW PROJECT

Portfolio