Run AI Models with IBM Watson Studio

machine learning algorithms

bits of code that incoporates both statistics and calculus to enable computers to learn from data and make predictions or decisions without explicit programming.

machine learning models

large-scale computer programs made up of machine learning algorithms

function

a set of logical operations that inputs some sort of data, analyzes or transforms it, and then outputs a result.

AutoAI

prepares raw data for machine learning. It can apply various algorithms to clean and structure the data, automatically select an appropriate model, and optimize its output for the fastest, most useful output.

Confusion Matrix

allows you to measure the performance of your model.

True Positive

The model predicts positive (Risk), and the result is positive (Risk).

False Positive

The model predicts positive (Risk), but the result is negative (No Risk).

False Negative

The model predicts negative (No Risk), and the result is positive (Risk).

True Negative

The model predicts negative (No Risk), and the result is negative (No Risk).

Jupyter Notebooks

allow you to collect all aspects of your project in one place, including code, graphics, text, and the output of the model

IBM Watson Studio

A cloud-based platform that provides tools for data scientists and developers to collaborate, build, and deploy machine learning models.