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  1. Skills Directory
  2. Machine Learning

Machine Learning

Intermediate

Machine Learning, a subdomain of artificial intelligence, allows computers to produce output without being explicitly programmed.

This competency area includes using One-Hot encoding technique, creating new features using feature engineering, record sampling, running inference on a pre-trained machine learning model, among others. 

Key Competencies:

  1. Transform features using the One-Hot encoding technique ​- Transforming categorical features to numerical features using the One-Hot encoding data transformation technique.

  2. Create new features using feature engineering - ​Transforming a single feature into multiple features so that a machine can easily find patterns in the data. For example, transforming a date timestamp to month, day of week, and time of day features.

  3. Perform record sampling​ - Removing observations based on business need and the business problem being solved.

  4. Split data for training and evaluation purposes ​- Performing an 80/20 split of data for training and evaluation purposes using Scikit-learn, a machine learning library for Python.

  5. Load pre-trained machine learning model​ - Selecting and loading a pre-trained Computer Vision machine learning model from Model Zoo.

  6. Run inference on pre-trained machine learning model ​- Running inference on a pre-trained machine learning model loaded from Model Zoo.