Table of Content
✓ Program with Oracle SQL and PL/SQL
✓ Create procedures, functions, packages, and triggers using PL/SQL
✓ Describe the components and feature of Oracle Machine Learning
✓ Use OML features with Oracle Autonomous Database
✓ Identify Oracle Cloud Services that are compatible with OML
✓ Create projects, workspaces, SQL scripts, job schedules, templates,
and notebooks in OML
✓ Describe OML use cases
A subset of artificial intelligence (AI), machine learning (ML) is the area of
computational science that focuses on analysing and interpreting patterns and structures in data to enable learning, reasoning, and decision making outside of human interaction. Simply put, machine learning allows the user to feed a computer algorithm an immense amount of data and have the computer analyse and make data-driven recommendations and decisions based on only the input data. If any corrections are identified, the algorithm can incorporate that information to improve its future decision making.
With Oracle Machine Learning, Oracle moves the algorithms to the data. Oracle runs machine learning within the database, where the data reside. This approach minimizes or eliminates data movement, achieves scalability, preserves data security, and accelerates time-to-model deployment. Oracle delivers parallelized in-database implementations of machine learning algorithms and integration with the leading open-source environments. Oracle Machine Learning delivers the performance, scalability, and automation required by enterprise-scale data science projects – both on-premises and in the Cloud.