Presented by:

4327055f5cebef343e46341d95f944af

Abbas Butt

EnterpriseDB

Abbas Butt (abbas.butt@enterprisedb.com) is a Senior Software Architect at EnterpriseDB.
He has been working for EnterpriseDB since Jan 2011.
He has over 25 years of product development experience.

  • Currently working on
    • Migration Portal for online schema migration from Oracle to PostgreSQL
    • xDB and EPRS Replication Server
    • Schema cloning with parallel data load
  • Previously worked on
    • XA Compliance for PostgreSQL
    • Postgres-XC
    • Packages for IBM DB2
      • UTL_ENCODE
      • UTL_TCP
      • UTL_SMTP
      • UTL_MAIL
    • Hospital Management System
    • Tele-medicine & Video Conferencing
    • Electronic Stethoscope
    • Accounts Management System
    • Payphone Management System
    • IVR based Telecom Billing System
    • Voice Communication System
    • Mobile Observer Unit Automation
    • 8051 micro controller based payphone

https://pk.linkedin.com/in/abbasbutt

No video of the event yet, sorry!

In today’s data-driven world, Machine Learning (ML) is transforming industries from predictive analytics in finance to real-time recommendations in e-commerce.
Wouldn't it be great if the database i.e. PostgreSQL, you're already using for storing data could also be used to implement ML capabilities?

In this training participants will get familiarity with implementing popular machine learning algorithms using PostgreSQL 15.10 and Apache MADlib 2.1.0 installed on Ubuntu 22.04.

Specifically the training will focus on the following topics:

  1. Introduction to Machine Learning (ML) 1.1 Traditional Algorithms vs ML Algorithms 1.2 Why implement ML Algorithms using PostgreSQL?

  2. Linear Regression Analysis 2.1. Setting up the dataset 2.2. Role of crosstab extension 2.3. Correlation Coefficient 2.4. Slope & Intercept 2.5. Generalizing Statistical Analysis

  3. Image Denoising 3.1. Apache MADlib 3.2. Introduction to MNIST dataset 3.2.1 Training, Validation and Testing 3.2.2 Importing images and labels into the database 3.2.3 Displaying the MNIST images 3.3. Adding Gaussian noise to the images 3.4. What is Singular Value Decomposition (SVD)? 3.5. Applications of SVD 3.6. Image Denoising using SVD MADlib functions

  4. Image Classification 4.1. Introduction to Neural Networks 4.2. What is classification? 4.3. Multilayer Perceptron 4.3.1 Input, Hidden and Output Layer 4.3.2 Training using Stochastic Gradient Descent (SGD) 4.4. Image classification with Multilayer Perceptron using mlp_* MADlib functions

  5. Other Important ML Algorithms

  6. Concluding Remarks

Date:
2025 March 18 13:00 EDT
Duration:
3 h
Room:
Gold Coast 1
Conference:
Postgres Conference 2025
Language:
Track:
Dev
Difficulty:
Medium
Requires Registration:
Yes (Registered: 1)