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Technologies / Artificial Intelligence

Machine learning with PredictionIO

The training provides advanced knowledge of building recommendation and prediction engines using Apache PredictionIO. Participants will learn how to create, deploy and manage ML engines in a production environment. The program combines theory with intensive hands-on workshops, covering the full lifecycle of an ML project from concept to deployment.The training focuses on building high-performance web applications using the OpenResty platform, which combines the capabilities of the Nginx server with the Lua programming language. During the hands-on workshop, participants will learn about the OpenResty architecture and how to create their own modules and extensions. The classes are conducted in the form of interactive workshops, where theory is immediately translated into practice through the implementation of real use cases.

Issues

  • PredictionIO architecture

  • Event Server

  • Predictive motors

  • Data processing

  • Recommendation algorithms

  • Evaluation of models

  • Deployment of systems

  • Performance monitoring

  • Scaling up solutions

  • Personalization

  • Real-time processing

  • Performance optimization

  • ----------|------------- Subcategory | Software Development Training code | IT-SD-460 Duration | 1 day (8 hours) Price net/person | 2650 PLN.

  • OpenResty architecture and components

  • Lua programming

  • Nginx integration with Lua

  • Create modules and extensions

  • Performance optimization

  • Caching and cache

  • Load balancing

  • Monitoring and debugging

  • Application security

  • Best implementation practices

  • Scalability of the application

  • Integration with external services

Benefits

  • The participant will gain the ability to design and implement advanced recommendation systems using PredictionIO
  • Will learn to create scalable ML engines tailored to specific business requirements
  • Will learn techniques for optimizing and monitoring the performance of predictive systems
  • Will be able to deploy and manage ML engines in a production environment
  • Will gain knowledge of integrating PredictionIO with existing infrastructure
  • Will develop the ability to create personalized recommendation systems.The participant will be able to independently design and implement high-performance web applications using the OpenResty platform
  • Will gain the ability to create custom modules to extend the functionality of the Nginx server
  • Will learn to optimize the performance of web applications by effectively utilizing the capabilities of OpenResty
  • Will learn techniques for debugging and monitoring applications in a production environment
  • Will know how to implement advanced caching and load balancing mechanisms
  • Web application security

Who is this training for?

ML engineers building recommender systems
Developers of applications using ML
Data Scientists implementing production models
ML systems architects
Personalization and recommendation specialists
Backend developers interested in ML
Web application developers looking for high-performance server solutions
System administrators interested in optimizing web infrastructure
DevOps engineers looking to expand their knowledge with high-performance solutions
Systems architects designing scalable web infrastructure
Web application performance specialists
Lua programmers looking to apply their skills in a web context

Prerequisites

  • Knowledge of the basics of machine learning
  • Programming experience in Scala or Java
  • Basic knowledge of distributed systems
  • Understanding recommendation algorithms
  • Knowledge of HTTP protocol basics and web application architecture
  • Basic knowledge of web servers, experience with Nginx preferred
  • General knowledge of programming (in any language)
  • Basic knowledge of Unix/Linux systems

Training program

01

Platform architecture

  • System components
  • Preparation of the environment
  • Event Server and Engines
  • Construction of prediction engines
  • Implementation of algorithms
  • Data processing
  • Evaluation of models
  • Parameter tuning
  • Deployment and scaling
02

Deployment of engines

  • Infrastructure management
  • Performance monitoring
03

High load handling

  • Personalization of recommendations
04

Real-time processing

  • Integration with external systems
  • Performance optimization
  • Introduction to OpenResty
  • Platform architecture and components
  • Nginx integration with Lua
  • HTTP request lifecycle
  • OpenResty basic configuration
  • Programming in Lua for OpenResty
  • Lua syntax and specifics
  • OpenResty modules and libraries
  • Handling HTTP requests
  • Memory and performance management
  • Create modules and extensions
  • OpenResty module structure
  • Implementation of own directives
  • Integration with external services
  • Module performance optimization
05

Advanced applications

  • Caching and cache
06

Load balancing

  • Monitoring and debugging
  • Application security

Delivery Methods

Online

  • Convenience of participating from anywhere
  • Interactive live sessions with trainer
  • Materials available for 30 days
  • No travel costs

On-site

  • Direct contact with trainer and group
  • Intensive hands-on workshops
  • Networking with other participants
  • Full focus on learning

Frequently asked questions

Who is the Machine learning with PredictionIO training for?

This training is designed for professionals looking to develop skills in machine learning with predictionio. Required level: advanced.

How long is the Machine learning with PredictionIO training?

The training lasts 3. Available in online or on-site format.

Will I receive a certificate?

Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.

Can this training be conducted for a closed group?

Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.

Kamil Gabryszewski
Kamil Gabryszewski Opiekun szkolenia

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Funding Options

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Up to 80%

Development Services Database

Up to 80% funding for SMEs from EU funds

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Up to 100%

National Training Fund

Up to 100% funding for employers

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We train teams at Poland's largest companies

ING Bank - EITT client
mBank - EITT client
PKO Bank Polski - EITT client
PZU - EITT client
Allianz - EITT client
T-Mobile - EITT client
KGHM - EITT client
PGE - EITT client
IKEA - EITT client
InPost - EITT client
Leroy Merlin - EITT client
ZUS - EITT client

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