I will build and train custom machine learning models in python
AI ML Developer, Python, OCR, Computer Vision and Data Processing
About this Gig
I will build, train, evaluate, and optimize custom machine learning models in Python based on your dataset and project requirements.
I can help with:
- Data cleaning and preprocessing
- Classification and regression
- Clustering and anomaly detection
- Feature selection and engineering
- Model training and evaluation
- Hyperparameter tuning
- Model comparison
- Performance metrics and visualizations
- Python source code
- Jupyter Notebook or Google Colab delivery
I work with Python, Scikit-learn, Pandas, NumPy, TensorFlow, and PyTorch.
I focus on clean, practical, and reproducible ML solutions. Model performance depends on the quality and size of the dataset, so I do not promise unrealistic accuracy.
Not sure which model you need? Send me your dataset or project details before ordering, and I can review the problem and suggest the right approach.
Programming language:
Python
Frameworks:
Scikit-learn
•
Keras
•
PyTorch
•
Panda
Tools:
Jupyter Notebook
•
OpenCV
•
TensorFlow
•
Excel
•
Colab
Other Data Science & ML Services I Offer
FAQ
What do you need from me before starting?
Please share your dataset, target column or expected output, problem description, and any specific requirements.
What types of machine learning models can you build?
I can work on classification, regression, clustering, anomaly detection, recommendation-related models, and predictive analysis.
Will I receive the source code?
Yes. Source code is included according to the package you choose.
Can you preprocess and clean my dataset?
Yes. I can handle missing values, encoding, scaling, feature preparation, and other preprocessing tasks.
Can you guarantee a specific accuracy?
No. Model performance depends on the dataset quality, size, features, and problem complexity. I will aim to build and evaluate the best suitable model for your data.
Should I contact you before ordering?
Yes. Please message me first so I can confirm the project scope, dataset requirements, and correct package.
