Himanshu Solanki
Turning Data into Smart, Scalable Solutions
About Me
AI & Machine Learning Engineer passionate about building smart, data-driven solutions that turn raw information into insights.
Skilled in Machine Learning, Deep Learning, and Data Analytics — from developing predictive models to creating interactive dashboards and intelligent systems.
Currently pursuing B.Tech in Computer Science and exploring Generative AI and RAG-based systems to build intelligent, context-aware applications.
Skills
Projects
1. Data Analytics (BI)
E-commerce Sales Dashboard
Designed an interactive Power BI dashboard with DAX measures to analyze sales performance, profits, and category trends, enabling data-driven insights for business decision-making.
Demo(Video)COVID-19 Global Dashboard
Developed a global COVID-19 monitoring dashboard using Power BI with dynamic date-slicers, trend analysis, and automated visual insights for global case tracking.
Demo(Video)2. Machine Learning (ML)
Smart Crop Prediction AI
Developed an ML classification model to recommend the best crop based on soil, climate, and environmental parameters. Deployed using Streamlit with real-time user input support.
Live AppMovie Recommendation
Created a content-based movie recommendation system using TF-IDF and Cosine Similarity to generate personalized movie suggestions. Deployed using Streamlit.
Live AppLoan Default Prediction
Built a Classification Model-based ML model to estimate the probability of loan default using customer details. Packaged into a clean Streamlit web app for real-time prediction.
Live AppRide Price Prediction
Built a regression-based ML model to predict ride fares using distance, time, weather, and city zone features. Deployed on Streamlit with real-time predictions.
Live AppInsurance Charges Prediction
Developed a regression model to predict medical insurance charges based on patient demographics and lifestyle features. Integrated with a Streamlit dashboard.
Live AppCar Price Prediction
Created a regression-based prediction system for estimating resale car prices using vehicle age, brand, and mileage. Deployed via Streamlit.
Live AppEmotion Detection from Text
Performed text emotion classification using NLP (NLTK, TextBlob) and ML (Scikit-Learn). The app analyzes user input and predicts emotional tone with high accuracy.
3. Deep Learning (DL)
Bank Churn Prediction
Built a neural network model to predict customer churn using TensorFlow/Keras. Deployed using Streamlit to provide quick predictions for customer retention strategies.
Live AppCat-Dog Classification
Developed a CNN using TensorFlow/Keras to classify cat and dog images. Trained on thousands of images for high-accuracy predictions and uploaded on GitHub.
Real-Time Weather Prediction
Integrated OpenWeather API and an LSTM model to forecast weather conditions in real-time. Visualized predictions on a modern Streamlit dashboard.
Live App