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I will build python machine learning models
About this Gig
I will develop Python-based Machine Learning and Deep Learning solutions tailored to your project requirements.
As a Computer Science graduate, I have hands-on experience building predictive models, classification systems, and AI-powered applications. I work with popular ML algorithms and frameworks to develop, train, test, and evaluate models using your dataset.
My services include:
- Machine Learning model development
- Classification and predictive analysis
- Regression and churn prediction
- Random Forest, XGBoost, and SVM
- Artificial Neural Networks (ANN)
- Data cleaning and preprocessing
- Feature engineering and selection
- Model evaluation and performance analysis
- Data visualization and reporting
Tools: Python, Scikit-learn, TensorFlow, Keras, PyTorch, Pandas, NumPy, and Jupyter Notebook.
You will receive clean, organized source code, model evaluation results, and documentation according to your package.
Please contact me before ordering so we can discuss your requirements and confirm the project scope.
Programming language:
Python
Frameworks:
Scikit-learn
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Keras
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PyTorch
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Panda
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Other
APIs:
Other
Tools:
Jupyter Notebook
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OpenCV
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TensorFlow
•
Excel
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Colab
•
Other
FAQ
What information do you need to start the project?
I need your dataset (if available), project requirements, expected output, and any specific algorithms or evaluation metrics you want me to use.
Can you build a machine learning model using my dataset?
Yes. I can analyze your dataset, preprocess the data, select suitable algorithms, train the model, and evaluate its performance.
Which machine learning algorithms do you work with?
I work with Random Forest, Decision Trees, XGBoost, SVM, classification and regression algorithms, ensemble learning, and Artificial Neural Networks and more.
Do you provide the source code?
Yes. I provide organized Python source code and relevant Jupyter Notebook files according to the selected package.
Do you guarantee a specific model accuracy?
No. Model accuracy depends on dataset quality, feature selection, data distribution, and the complexity of the problem. I focus on appropriate model selection and reliable evaluation rather than promising unrealistic accuracy.
Can you explain the results of the model?
Yes. I can provide evaluation metrics such as accuracy, precision, recall, F1-score, confusion matrices, and visualizations, depending on the project.
Can you work on an existing machine learning project?
Yes. I can review existing code, troubleshoot issues, improve preprocessing, and help optimize model performance within the agreed scope.
Do you accept custom machine learning projects?
Yes. Contact me before ordering with your requirements so I can assess the complexity, timeline, and appropriate package.
