You will get a production-ready AI and machine learning solution for your business
Project details
I will develop a custom AI or machine learning solution tailored to your business problem, dataset, and technical requirements. Depending on the selected package, the project may include data preparation, feature engineering, model development, hyperparameter tuning, validation, performance visualizations, documentation, source code, API integration, and deployment-ready components.
I work with Python, TensorFlow, PyTorch, scikit-learn, pandas, NumPy, OpenCV, FastAPI, and related tools to build classification, prediction, computer vision, NLP, anomaly detection, and other intelligent systems.
You will receive clean, organized, and maintainable work with transparent evaluation results. I do not promise unrealistic accuracy before reviewing the data. Instead, I select appropriate metrics, compare suitable approaches, explain limitations, and deliver a solution aligned with your practical goals.
I work with Python, TensorFlow, PyTorch, scikit-learn, pandas, NumPy, OpenCV, FastAPI, and related tools to build classification, prediction, computer vision, NLP, anomaly detection, and other intelligent systems.
You will receive clean, organized, and maintainable work with transparent evaluation results. I do not promise unrealistic accuracy before reviewing the data. Instead, I select appropriate metrics, compare suitable approaches, explain limitations, and deliver a solution aligned with your practical goals.
Machine Learning Tools
Amazon SageMaker, Keras, Kubeflow, MLflow, NLTK, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, TensorFlow, Tesseract OCR, Vertex AI, XGBoostWhat's included
| Service Tiers |
Starter
$300
|
Standard
$750
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 2 | 4 | 5 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Additional Revision
+$50
Additional Model Variation
(+ 2 Days)
+$150
Additional Scenario
(+ 2 Days)
+$100
Additional Graph/Chart
(+ 1 Day)
+$30
Model Documentation
(+ 2 Days)
+$100
Data Source Connectivity
(+ 2 Days)
+$200
FastAPI integration
(+ 3 Days)
+$250
Docker setup
(+ 2 Days)
+$150
Cloud deployment support
(+ 3 Days)
+$300Frequently asked questions
About Fandishe
Software Engineer | AI Engineer | Backend Engineer
Konya, Turkey - 6:17 am local time
I can help you with:
Backend development using Spring Boot or FastAPI
REST and GraphQL API design and integration
JWT authentication and role-based access control
Microservices and event-driven architectures
MongoDB and PostgreSQL database development
RabbitMQ, Kafka, and gRPC integration
Machine learning model development and deployment
AI-powered classification, prediction, and automation systems
Debugging, testing, Dockerization, and performance optimization
My project experience includes inventory management systems, secure authentication platforms, fraud-monitoring applications, malicious URL detection systems, medical image classification, and AI-enabled backend services.
I previously worked as a Software Engineer at Cooperative Bank of Oromia and hold a Bachelor’s degree in Software Engineering with honors. I am also completing a Master’s degree in Software Engineering at Konya Technical University, Turkiye.
I value clean code, secure architecture, clear communication, and dependable delivery. My goal is to understand your requirements carefully and provide a maintainable solution that supports the long-term growth of your project.
Steps for completing your project
After purchasing the project, send requirements so Fandishe can start the project.
Delivery time starts when Fandishe receives requirements from you.
Fandishe works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements and data review
I will review your goals, dataset, expected output, success criteria, and integration requirements, then confirm the final scope.
Data preparation and solution design
I will clean and prepare the data, examine its quality, select appropriate features, and design the machine learning workflow.