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$
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I will build custom ml regression models for your data
About this Gig
I will build a custom machine learning regression model to predict outcomes based on your data, using Python and popular libraries like scikit-learn, TensorFlow or PyTorch.
Basic: Build a single model with basic preprocessing (e.g., handling missing values, encoding, scaling) and standard evaluation metrics including MAE, MSE. Ideal for clean, small-to-medium datasets (up to 10k rows).
Standard: Develop and compare multiple models. Includes enhanced preprocessing with missing data imputation and feature selection, along with performance comparison using various metrics. Suitable for datasets up to 50k rows.
Premium: Designed for complex or high-dimensional datasets. Includes advanced preprocessing (e.g., outlier handling, feature engineering, advanced encoding), and a basic deployment for testing or integration.
Basic deployment is included in the Premium package and available as an extra service for Basic and Standard packages.
Programming language:
Python
•
SQL
•
Colab
•
MLflow
Frameworks:
Scikit-learn
•
Keras
•
PyTorch
•
Panda
•
Other
Tools:
TensorFlow
•
Excel
•
MLflow
•
Colab
FAQ
What kind of problems can you help with?
Any task where the output is a numeric value. For example: predicting housing, energy consumption, pollution levels, etc.
What will I receive?
You’ll receive the trained model (or code to train it), evaluation metrics, visualizations, and optionally a notebook or script with explanations and instructions.
Can you help clean and prepare the data?
Yes! I offer data preprocessing, feature selection, handling missing values, encoding categorical variables, and more.
What if my dataset is too large or the task is very complex?
If your dataset is very large, high-dimensional, or if the task involves complex modeling I may suggest using cloud services such as AWS or Google Colab Pro to ensure efficient training. I will guide you through the process or handle it myself if access is provided.
Do you provide the source code?
Yes! You will receive clean, well-documented Python code that you can reuse and modify.
What do I need to provide to get started?
Your dataset (in CSV or Excel), a description of the target variable (what you want to predict), and any relevant business context (e.g. what the data means). If you're unsure, I can help guide you through it.
What kind of models do you use?
I use a variety of machine learning regression models depending on your data: Linear regression, tree-based models (like Random Forest or XGBoost), SVM, deep neural networks, or ensamble.
Do you offer model deployment?
Basic deployment is included in the Premium package and available as an extra service for Basic and Standard packages.
Do you include hyperparameter tuning?
Hyperparameter tuning can be computationally expensive depending on the complexity of the task and the size of the dataset. Feel free to ask whether it is included for your specific project.
What tools or libraries do you use?
Primarily Python with libraries such as scikit-learn, XGBoost, TensorFlow or PyTorch, MLflow, pandas, matplotlib, seaborn, scipy.
