unsupervised learning

mentoring

reinforcement learning

supervised learning

Support Vector Machines

Naive Bayes classification

Logistic regression

Linear regression

trend, noise, covariance

trend, noise, kurtosis

trend, seasonality, causation

trend, seasonality, noise

constant attention needed for maintenance and support of the cloud platform

capable of managing and handling dynamic workloads with automatic recovery from failures

hybrid clouds enable the deployment of distributed large neural networks

support for common business oriented language (COBOL) applications

the hardware requirement can be scaled up as per the demand

CSV files cannot be used as data sources in Watson Studio.

The CSV file was converted to a binary blob and must be converted in the notebook code.

The CSV file is stored in a Cloud Object Storage.

The CSV file is stored in a Watson Machine Learning instance and is only accessible via REST API.

The use case requires a 100% likelihood of making a correct/true prediction.

Training and testing data for the model contain outliers.

Data for the machine learning model is available only as static CSV files.

The neural network for the model requires significantly more computing power than a logistic regression model.