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Fiverr Pro
English
$
USD
I will build predictive machine learning models for classification and regression
About this Gig
Need a machine-learning model that turns your data into useful predictions?
I will build a custom classification or regression model using your structured/tabular dataset and provide clear evaluation, reproducible Python code, and documented results.
I can help with:
- Classification and regression
- Data cleaning and preprocessing
- Exploratory data analysis
- Feature preparation and engineering
- Model comparison and validation
- Random Forest, XGBoost, regression and other suitable ML models
- Evaluation metrics and error analysis
- Feature importance and model interpretation
- Reproducible notebooks and source code
- Batch inference or API prototype on higher packages
Please contact me before ordering if your dataset requires extensive cleaning, multiple data sources, deep learning, NLP, time-series forecasting, cloud deployment, or large-scale processing.
Results depend on your dataset and evaluation setup, so specific accuracy or business outcomes cannot be guaranteed.
Programming language:
Python
•
R
•
MATLAB
•
SQL
Frameworks:
Scikit-learn
•
Keras
•
PyTorch
•
Panda
•
Other
Tools:
Jupyter Notebook
•
OpenCV
•
OpenNN
•
TensorFlow
•
Excel
•
Colab
FAQ
What types of machine-learning problems can you work on?
This Gig focuses on supervised machine-learning problems using structured/tabular data, primarily classification and regression. Please contact me first for time-series forecasting, NLP, computer vision, deep learning, or unusual data types.
What is classification?
Classification predicts a category or class, such as churn/no churn, fraud/not fraud, approved/rejected, or one category among several possible classes.
What is regression?
Regression predicts a numerical value, such as a price, demand level, score, revenue amount, or another continuous target.
What data should I provide?
Please provide a structured dataset such as CSV, Excel, or another agreed tabular format together with a description of the columns and the target you want to predict.
Can you clean my dataset?
Cleaning is included within the package limits. Extensive cleaning, merging many data sources, manual labeling, or rebuilding severely incomplete datasets may require a custom offer.
Which machine-learning algorithms will you use?
The algorithm depends on your dataset and prediction task. Suitable approaches may include regression models, decision trees, Random Forest, gradient boosting, XGBoost, and other appropriate classical machine-learning methods.
Can you guarantee a specific accuracy?
No. Model performance depends heavily on the quality, quantity, relevance, balance, and predictability of the supplied data. I will use appropriate evaluation methods and clearly report the achieved results.
Will I receive the source code?
Yes. You will receive the reproducible Python code or notebook included in your package, along with relevant model artifacts and documentation.
Can you deploy the model?
The Premium package include inference API prototype or batch prediction script. Full cloud deployment, monitoring, scalable infrastructure, and ongoing MLOps are separate services.
