You will get get a custom machine learning model with actionable insights
Project details
You will get a custom machine learning model tailored to your data and business goals. I combine strong statistical foundations with industry experience to deliver clean code, insightful results, and visualizations that make sense. Whether you're looking for predictions, classifications, or pattern detection, I ensure your project is handled with care, clarity, and precision.
Machine Learning Tools
Amazon SageMaker, NumPy, pandas, Python, Python Scikit-Learn, SQL, XGBoostWhat's included $40
These options are included with the project scope.
$40
- Delivery Time 7 days
- Number of Revisions 1
- Number of Model Variations 1
- Number of Scenarios 1
- Number of Graphs/Charts 2
- Model Validation/Testing
- Model Documentation
About Nisha
Data Scientist & Analyst | Python, SQL, Tableau, ML Models
Danville, United States - 6:32 pm local time
I’m Nisha, a data scientist and analyst with real-world experience turning raw, chaotic datasets into clear, actionable stories that drive results. I’ve built machine learning models that uncovered over $1M+ in potential cost savings, automated ETL pipelines with Python and SQL, and developed dashboards to help leaders make smarter decisions—fast.
💡 Here’s what I can do for you:
Predictive modeling (regression, classification, forecasting)
Interactive dashboards with Tableau or Qlik Sense
Automated reporting pipelines using Python, SQL, R
Cleaning, wrangling, and transforming your data for impact
🛠 Tech stack: Python, SQL, R, Excel, Tableau, Qlik Sense, Machine Learning
📊 Clear communication. Fast delivery. Actionable insights. Every time.
Let’s talk about your data goals and how I can help you crush them.
Steps for completing your project
After purchasing the project, send requirements so Nisha can start the project.
Delivery time starts when Nisha receives requirements from you.
Nisha works on your project following the steps below.
Revisions may occur after the delivery date.
Steps
• Review your dataset and objectives • Preprocess data and engineer features • Build and train the machine learning model • Evaluate performance using key metrics • Share draft results and collect feedback • Finalize and deliver model and insights