You will get Interactive Heart Disease Prediction App | Machine Learning & Streamlit
Project details
Project Description:
Developed a functional, end-to-end medical diagnostic tool that predicts the likelihood of heart disease in patients based on clinical parameters (Age, Cholesterol, Max Heart Rate, etc.).
The Challenge:
To turn a complex health dataset into a user-friendly tool that provides instant, accurate predictions without requiring the user to understand the underlying math.
My Solution:
Data Analysis: Performed EDA using Pandas and Seaborn to identify key heart disease indicators.
Model Development: Trained a K-Nearest Neighbors (KNN) classifier, optimizing for high recall to ensure potential risks aren't missed.
Interactive UI: Built a web interface using Streamlit, allowing users to input data via sliders and dropdowns.
Deployment: Hosted the live app for real-time access.
Tools Used:
Python, Scikit-learn, Pandas, Streamlit, Matplotlib.
Developed a functional, end-to-end medical diagnostic tool that predicts the likelihood of heart disease in patients based on clinical parameters (Age, Cholesterol, Max Heart Rate, etc.).
The Challenge:
To turn a complex health dataset into a user-friendly tool that provides instant, accurate predictions without requiring the user to understand the underlying math.
My Solution:
Data Analysis: Performed EDA using Pandas and Seaborn to identify key heart disease indicators.
Model Development: Trained a K-Nearest Neighbors (KNN) classifier, optimizing for high recall to ensure potential risks aren't missed.
Interactive UI: Built a web interface using Streamlit, allowing users to input data via sliders and dropdowns.
Deployment: Hosted the live app for real-time access.
Tools Used:
Python, Scikit-learn, Pandas, Streamlit, Matplotlib.
Machine Learning Tools
NumPy, pandas, Python, Python Scikit-Learn, scikit-learn, SciPyWhat's included
| Service Tiers |
Starter
$20
|
Standard
$35
|
Advanced
$65
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 5 days |
Number of Revisions | 1 | 2 | 2 |
Number of Graphs/Charts | 5 | ||
Model Validation/Testing | - | - | |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - |
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Source Code
+$10About Sium Aameed
Data Science Specialist: From Cleaning to ML Deployment
Mohammadpur, Bangladesh - 10:30 am local time
Hi! I’m a Data Specialist with a deep background in Statistics. I bridge the gap between raw, messy data and functional business tools by building everything from automated cleaning pipelines to live predictive web apps.
Expertise:
Processing: Advanced Wrangling (Pandas, NumPy, SQL).
Intelligence: Machine Learning & Predictive Modeling (Scikit-learn).
Deployment: Live Interactive Apps (Streamlit).
Visualization: High-impact Storytelling (Plotly, Seaborn,SPSS).
Why Choose Me:
- I turn complex data into clear, actionable insights.
- Skilled in Python, pandas, numpy, matplotlib, seaborn, plotly and sql.
- Experienced in data cleaning, analysis, visualization, and dashboards.
- I handle projects end-to-end with regular, clear communication.
- Reliable, detail-oriented, and focused on delivering results that matter.
You'll get accurate work, delivered fast. I pride myself on creating clear, understandable results.
Ready to find your data's potential?
Send me a message!
Steps for completing your project
After purchasing the project, send requirements so Sium Aameed can start the project.
Delivery time starts when Sium Aameed receives requirements from you.
Sium Aameed works on your project following the steps below.
Revisions may occur after the delivery date.
Data Cleaning
EDA