Machine Learn GPT-Machine Learning Assistance

Example

Automatically handling missing values or encoding categorical variables in a dataset.

Scenario

A user uploads a dataset with missing entries and several categorical features. Machine Learn GPT could suggest techniques like K-nearest neighbors for imputation and advise on one-hot encoding for the categorical variables to prepare the data for machine learning models.

Example

Generating insightful visualizations such as correlation heatmaps, distribution plots, and feature importance graphs.

Scenario

For a dataset involving customer demographics and buying habits, Machine Learn GPT can generate visual plots to show the relationships between age, income level, and purchasing patterns, aiding in the understanding of key market segments.

Example

Providing code snippets to train machine learning models using libraries like scikit-learn or TensorFlow.

Scenario

A user is trying to predict customer churn based on website engagement metrics. Machine Learn GPT can provide a step-by-step guide to train a logistic regression model, including how to split the data, train the model, and evaluate its performance using metrics like ROC-AUC.

Example

Guiding users through the process of setting up and running AutoML tasks to find the best model automatically.

Scenario

A small business owner without much background in data science wants to forecast monthly sales. Machine Learn GPT can guide them in setting up an AutoML pipeline that automatically tests multiple models and hyperparameters to identify the one that performs best.