I will build and train a machine learning model using python scikit learn or pytorch

Have data and a question you want it to answer, like which customers will churn, what sales will be next month, or which category a record belongs to?

I will build and train a custom machine learning model in Python on your dataset, and explain the results in plain language.

What I do:

• Data cleaning, preprocessing and feature engineering
• Train and compare models: Logistic Regression, Random Forest, SVM, XGBoost, Neural Networks (PyTorch)
• Evaluate with accuracy, precision, recall, F1 and a confusion matrix
• Tune hyperparameters for better performance
• Save the trained model so you can reuse it on new data

Example use cases:

• Customer churn prediction
• Sales or demand forecasting
• Spam and text classification
• Tabular classification and regression
• Image classification (PyTorch CNN)

You receive:

• Jupyter Notebook or Python script with comments
• Trained model file (.pkl or .pt)
• Results report (PDF or Markdown) with charts

Tech: Python, scikit-learn, PyTorch, Pandas, NumPy, XGBoost, Matplotlib

Please message me with your dataset and goal first so I can confirm the right approach.