Python Classification Model Development
Budget: ₹600 – ₹1,500 INR
I am looking for an AI/ML developer to help with a small Python-based data analysis and machine learning task. The work involves exploring a raw dataset, cleaning it, preparing useful features, building a simple model, and evaluating the results.
The main focus is practical data analysis, clean code, and a lightweight machine learning workflow.
Responsibilities
Inspect and understand the dataset
Clean the data and handle missing or inconsistent values
Engineer useful features where needed
Create simple visualizations to understand key patterns
Build a basic machine learning pipeline in Python
Train and compare at least one simple baseline model with an improved model
Evaluate the model using suitable performance metrics
Save the final trained model for later use
Add clear comments so the code is easy to understand and reuse
Preferred Skills
Python
pandas and NumPy
scikit-learn or similar ML libraries
matplotlib / seaborn
Data cleaning and exploratory data analysis
Basic machine learning model development
Expected Deliverable
A clean and reproducible Python script or notebook that runs end-to-end, including data cleaning, analysis, feature preparation, model training, evaluation, and model saving.
Acceptance Criteria
Code should be simple, readable, and easy to run
The workflow should be clearly explained with comments
The improved model should perform better than the baseline
Final output should include evaluation metrics and a short summary of important features and next-step suggestions
This is a small task, so I am looking for someone who can keep the solution lightweight, practical, and well-documented.
The main focus is practical data analysis, clean code, and a lightweight machine learning workflow.
Responsibilities
Inspect and understand the dataset
Clean the data and handle missing or inconsistent values
Engineer useful features where needed
Create simple visualizations to understand key patterns
Build a basic machine learning pipeline in Python
Train and compare at least one simple baseline model with an improved model
Evaluate the model using suitable performance metrics
Save the final trained model for later use
Add clear comments so the code is easy to understand and reuse
Preferred Skills
Python
pandas and NumPy
scikit-learn or similar ML libraries
matplotlib / seaborn
Data cleaning and exploratory data analysis
Basic machine learning model development
Expected Deliverable
A clean and reproducible Python script or notebook that runs end-to-end, including data cleaning, analysis, feature preparation, model training, evaluation, and model saving.
Acceptance Criteria
Code should be simple, readable, and easy to run
The workflow should be clearly explained with comments
The improved model should perform better than the baseline
Final output should include evaluation metrics and a short summary of important features and next-step suggestions
This is a small task, so I am looking for someone who can keep the solution lightweight, practical, and well-documented.