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Predictive Modeling Applications Development with Streamlit: A Gentle Start with Data Science and Machine Learning Projects in Python
Learn how to build interactive data science applications with Streamlit—step by step!
Are you looking for a beginner-friendly guide to data science projects, machine learning apps, and interactive dashboards? This book shows you exactly how to turn datasets into professional Streamlit apps that you can deploy and share. With hands-on projects and real-world examples, you’ll move from basic exploratory data analysis (EDA) to building apps that demonstrate your skills in Python, data science, and machine learning.
Projects you will build in this
Titanic Dataset App – Explore and visualize passenger data in an interactive Streamlit dashboard.
California Housing Price Prediction App – Use regression models to predict housing prices based on dataset features.
Heart Disease Prediction App – Apply machine learning classification to predict the likelihood of heart disease.
Enhancing Apps – Improve apps with advanced Streamlit features, better visuals, and user interactivity.
Portfolio & Professional Deployment – Package and deploy your Streamlit apps to share with clients, employers, or the public.
Why this book?
Whether you are a student, data enthusiast, or professional, this book will help you learn how to create data apps with Streamlit, build a portfolio, and take your data science journey to the next level.
Get your copy today and start building powerful Streamlit apps with Python!
Are you looking for a beginner-friendly guide to data science projects, machine learning apps, and interactive dashboards? This book shows you exactly how to turn datasets into professional Streamlit apps that you can deploy and share. With hands-on projects and real-world examples, you’ll move from basic exploratory data analysis (EDA) to building apps that demonstrate your skills in Python, data science, and machine learning.
Projects you will build in this
Titanic Dataset App – Explore and visualize passenger data in an interactive Streamlit dashboard.
California Housing Price Prediction App – Use regression models to predict housing prices based on dataset features.
Heart Disease Prediction App – Apply machine learning classification to predict the likelihood of heart disease.
Enhancing Apps – Improve apps with advanced Streamlit features, better visuals, and user interactivity.
Portfolio & Professional Deployment – Package and deploy your Streamlit apps to share with clients, employers, or the public.
Why this book?
Whether you are a student, data enthusiast, or professional, this book will help you learn how to create data apps with Streamlit, build a portfolio, and take your data science journey to the next level.
Get your copy today and start building powerful Streamlit apps with Python!
79 pages, Kindle Edition
Published October 1, 2025
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