You will get a Custom Machine Learning Model for Classification or Prediction
Project details
You will get a custom machine learning model designed to solve your specific business or research problem using proven, industry-standard techniques. I focus on building practical, explainable, and well-evaluated models rather than black-box solutions.
Before training, I carefully analyze and preprocess your data to ensure quality and reliability. I then select the most suitable algorithm for your use case, train the model and evaluate its performance using appropriate metrics such as accuracy, precision, recall, F1-score or error rates. Clear visualizations and charts are included so results are easy to understand, even for non-technical stakeholders.
You will receive the complete source code, model files and clear documentation explaining how the model works, how results were achieved, and how it can be reused or extended. My approach emphasizes clarity, reproducibility and real-world usability.
This service is ideal for classification or prediction tasks such as customer churn analysis, risk scoring, sentiment analysis, demand forecasting or academic projects.
Before training, I carefully analyze and preprocess your data to ensure quality and reliability. I then select the most suitable algorithm for your use case, train the model and evaluate its performance using appropriate metrics such as accuracy, precision, recall, F1-score or error rates. Clear visualizations and charts are included so results are easy to understand, even for non-technical stakeholders.
You will receive the complete source code, model files and clear documentation explaining how the model works, how results were achieved, and how it can be reused or extended. My approach emphasizes clarity, reproducibility and real-world usability.
This service is ideal for classification or prediction tasks such as customer churn analysis, risk scoring, sentiment analysis, demand forecasting or academic projects.
Machine Learning Tools
BERT, Google Data Studio, Keras, NumPy, pandas, Python, Python Scikit-Learn, SciPy, TensorFlowWhat's included $100
These options are included with the project scope.
$100
- Delivery Time 5 days
- Number of Revisions 2
- Number of Model Variations 1
- Number of Scenarios 1
- Number of Graphs/Charts 3
- Model Validation/Testing
- Model Documentation
- Source Code
About Lewis
Junior Software Engineer | AWS Certified | Python
Nairobi, Kenya - 1:50 pm local time
Python & Backend Development
🔹 Developed and deployed FastAPI and Django backends that handle data intake, process inputs and return clean, structured outputs through REST APIs. Written with maintainability in mind not just to run once.
Applied Machine Learning
🔹 Built end-to-end ML pipelines covering data cleaning, feature engineering, model training and evaluation through to deployment. Worked with satellite NDVI and rainfall datasets via Google Earth Engine to train conflict-risk forecasting models. Integrated a live emotion-detection model into an Android application, served through a custom FastAPI backend returning predictions with confidence scores.
Cloud & AWS
🔹 Certified in AWS core services covering compute, storage, networking, IAM and cost management. Deployed cloud-connected applications using Firebase and Google Cloud Platform, with architecture planned for reliability and scalability from the start.
Technical focus:
Python · Django
Scikit-learn · Google Colab
Streamlit · Firebase
AWS core services · Git
Takes on projects that can be delivered properly. Communicates clearly about what is realistic. Focused on building things that hold up under real conditions, not just in a controlled environment.
Open to Python development, machine learning integrations and cloud-connected backend work.
Steps for completing your project
After purchasing the project, send requirements so Lewis can start the project.
Delivery time starts when Lewis receives requirements from you.
Lewis works on your project following the steps below.
Revisions may occur after the delivery date.
3
I clean and preprocess the data, train the machine learning model, evaluate performance, and prepare the final deliverables.