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Oracle Machine Learning with Oracle Cloud : An Introduction

Name: Oracle Machine Learning with Oracle Cloud : An Introduction
Rating: 3.5 (17 reviews)

Oracle Machine Learning : Explore & learn to use SQL, Python, AutoML using OML notebook on Oracle Cloud Infrastructure

Created byGuha Rajan M., B.Engg, MBA

Last updated 7/2022

English

English [Auto],

What you'll learn

Explore, learn & become an expert in Oracle Machine learning on Oracle Cloud Infrastructure using SQL, Python, Auton ML features
Learn to use Oracle Machine Learning notebook available on Oracle Cloud Infrastructure
Learn to Provision Oracle Autonomous Database on Oracle Cloud Infrastructure.
Get an Quick Overview about Machine Learning technique.

Course content

11 sections • 32 lectures • 3h 53m total length

Topics of Course Coverage5:37
Compare OLTP and OLAP, and explore Oracle machine learning on the autonomous database, provisioning cloud access, and using notebooks, SQL, Python, and AutoML for building, deploying, and visualizing models.
Business System - OLTP & OLAP14:51
Explore how enterprise resource planning integrates finance, purchasing, manufacturing, inventory and sales with OLTP for day-to-day transactions, and how OLAP enables business intelligence, analytics, and reporting through data consolidation.
Programming Vs Machine learning - Difference7:40
Understand how programming differs from machine learning by exploring data, model creation, training, and deployment, including supervised and unsupervised learning, classification, and model evaluation.
Different types of Machine Learning - Quick Overview12:35
Explore the five types of machine learning—supervised, unsupervised, reinforced, deep learning, and deep reinforcement learning—and how Oracle machine learning uses database data for models, classification, and regression.
Quiz 1

Getting access to Oracle cloud Infrastructure - Free tier - Part14:42
Explore how to access Oracle Cloud Infrastructure, sign up for the always free tier, and use two Linux compute virtual machines and autonomous database for learning or prototyping.
Getting access to Oracle cloud Infrastructure - Part 25:36
Learn how to create an Oracle cloud infrastructure account, validate a credit card with a verification charge, and start a 30-day free trial for database, virtual machines, and machine learning.

Creating OCI compartment and provisioning Autonomous Oracle DB10:15
Create an OCI compartment and provision an autonomous Oracle database in Oracle Cloud through self-service, and explore the differences between data warehousing and transaction processing.
Navigation with Oracle Autonomous DB8:06
Navigate Oracle Autonomous Database through a web-based interface, access database actions, development tools, and data loading, and explore Oracle Machine Learning notebooks with Python and SQL access.
Downloading DB wallet file & connecting to DB with client SQL developer6:35
Learn to download the DB wallet file, configure a cloud wallet, and connect to the Oracle autonomous database using SQL developer, and test the connection.
Quiz 2

Oracle Machine Learning - Quick Overview3:27
Discover how Oracle machine learning runs on the Oracle Autonomous database, using a Zeppelin notebook with interpreter bindings for SQL, PL SQL, and Python to run analytics.
Logging into Oracle Machine Learning7:34
Log into Oracle machine learning with the admin account, create a user, then use that account to access notebooks and prebuilt examples, exporting and re-importing notebooks as needed.
Creating Machine Learning notebook & users6:59
Learn to create and manage Oracle machine learning notebooks and users in Oracle Cloud, explore sql and Python workflows, and export-import notebooks to enable data selection and AutoML experiments.
Export & import of ML notebook6:59
Create a user and log in to Oracle machine learning on Oracle Cloud, then export and import notebooks to switch between SQL and Python workflows.
Text , Select & Check box option as input in Notebook4:42
Learn to capture runtime input in a notebook using text input, list box, dropdown, and checkbox forms. Explore selecting database objects such as tables and views by user input.

Providing user priviledge to ML user to acess though SQL developer6:00
Learn to grant appropriate privileges to a machine learning user via database API and SQL scripts, enable login with admin privileges, and use the machine learning console to upload data.
Table dataload directly using GUI in OCI6:08
Discover how to load a CSV file directly into an OCI table using the UI data load, validating a 100k record upload and comparing to SQL loader approaches.
Data visualization with the uploaded Table date8:05
Explore data visualization in Oracle machine learning using SQL and notebooks to create views, query credit rating data, and visualize by marital status and occupation with pie charts.
Quiz3

Oracle Machine Learning using SQL: Introduction7:22
Explore how Oracle machine learning with the Oracle Cloud enables time series forecasting using triple exponential smoothing, using the create model procedure to build and deploy models from database data.
Machine learning - Time series - Demonstration Part 15:18
Demonstrates time series forecasting in Oracle Cloud Machine Learning using exponential smoothing on autonomous database sales data, with exporting, importing, and running a time series notebook.
Machine learning - Time series - Demonstration - Part 28:29
Run and demonstrate time series forecasting using Oracle machine learning by creating views, executing models, and charting forecasts with upper and lower bounds.

Oracle Machine Learning - User guide as reference for learning3:46
Download the Oracle machine learning for Python user guide from Oracle (HTML or PDF) to learn moving data between Oracle Autonomous database and Python, and syncing with a DataFrame proxy.
Oracle Machine Learning - Built in Python Libraries4:49
Access the Oracle machine learning notebook on the autonomous database to use built-in Python libraries without installation, enabling direct import of pandas, numpy, and other tools in the cloud.
Using Python for Autonomous DB data visualization8:08
Explore using Python in the wMl notebook to work with the autonomous database, create and populate tables from a dataset, and visualize data with charts and slice‑and‑dice analysis.
Anamoly Detection - Support Vector Machine using Oracle Machine Learning - Part5:57
Explore anomaly detection with a one-class support vector machine in Oracle Machine Learning to identify rare records using database data as the truth source.
Anamoly Detection - Support Vector Machine using Oracle Machine Learning - Part13:05
Apply Oracle machine learning to perform anomaly detection with a support vector machine on merged customer and supplementary demographics data, visualize distributions, and review top predicted anomalies.

Oracle AutoML feature : An Overview5:34
Explore Oracle AutoML, a no-code UI introduced in early 2021 that lets business users create and deploy ML models, with automated algorithm selection, feature selection, and tuning.
Oracle Auto ML: Create Experiment using AutoML9:54
Create an Oracle AutoML experiment with the customer 360 data joined to demographics to predict affinity card. Run three models and identify key predictors like marital status and occupation.
Oracle AutoML : Deployment of Model & Creation of Notebook5:45
Quiz 4

Overview about JOB scheduling and creating OML notebook for demonstration7:05
Create an Oracle machine learning notebook and schedule it to automatically run select, create table, and copy statements against large autonomous database tables, enabling late-night data processing.
JOB creation and scheduling .5:49
Schedule a notebook job in Oracle machine learning by selecting the notebook, setting the run time in Europe/Dublin time zone, and enabling automatic daily execution.

Requirements

Basic Knowledge on SQL & Python would benificial
Access to Oracle Cloud Infrastructure, atleast the Oracle Cloud - always free tier.

Description

Oracle Machine Learning accelerates the creation and deployment of machine learning models for data scientists by eliminating the need to move data to dedicated machine learning systems.

Its available on Oracle Autonomous Database even with Oracle Cloud - Always Free tier.

This makes learning easier too without any local install.

OML Notebooks:

Data scientists and developers develop analytical solutions through an easy-to-use, multiuser collaborative interface based on Apache Zeppelin notebook technology,

supporting interpreters for Python, SQL, and PL/SQL on Oracle Autonomous Database.

OML for SQL:

SQL and PL/SQL users leverage in-database computation for data preparation & exploration, machine learning model building, evaluation, and deployment.

Leverage scalable in-database machine learning algorithms and make predictions directly in SQL queries.

OML for Python:

Python users gain the performance and scalability of Oracle Database (on premises) and Oracle Autonomous Database for data exploration, preparation, and machine learning from

a well-integrated Python interface with support for AutoML and immediate deployment of user-defined Python functions from REST endpoints.

OML AutoML User Interface:

A no-code user interface supporting AutoML on Autonomous Database to improve both data scientist productivity and non-expert user access to powerful in-database algorithms for classification and regression.

The Course has following topics of coverage:

•OLTP Vs OLAP.

•Programming vs Machine Learning

•Types of Machine Learning.

•Getting Access to OCI.

•Provisioning Oracle Autonomous Database.

•Oracle Machine Learning Overview.

•Logging into Machine Learning Console, Navigation & Creation of user

•Overview about Zeppelin Notebook

•SQL based

•Data visualization.

•Machine Learning.

•Using Python in Oracle Machine learning.

•Auto ML Experiment Provisioning & Execution

•Deployment of Model.

•Job Schedule of OML note book.

Happy Learning

Who this course is for:

IT Analysts
IT Professionals
Business & Data Analysts
Business Executives

Oracle Machine Learning with Oracle Cloud : An Introduction

What you'll learn

Explore related topics

Course content

Introduction4 lectures • 41min

Getting access to Oracle Cloud Infrastructure : Free tier2 lectures • 10min

Getting started with Oracle Cloud Infrastructure and provisioning autonomous DB.3 lectures • 25min

Getting Started with Oracle Machine Learning5 lectures • 30min

Data visualization with Oracle Machine learning - Demostration 11 lecture • 13min

Data visualization with Oracle Machine Learning - Demostration 23 lectures • 20min

Oracle Machine learning using SQL - Time series3 lectures • 21min

Oracle Machine Learning Using Python5 lectures • 36min

AutoML on OCI: Quickly and easily deploy reliable machine learning models on OCI3 lectures • 21min

Creating & Scheduling Notebook based JOB for Auto execution2 lectures • 13min

Requirements

Description

Who this course is for: