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Technologies / Artificial Intelligence

Apache Spark MLlib - large-scale machine learning

The training provides an in-depth understanding of the Apache Spark MLlib library in the context of machine learning on large datasets. The program covers both the theoretical foundations of the algorithms and the practical aspects of implementing them in a distributed environment. Participants will learn advanced techniques for optimizing and scaling ML models and best practices for implementing production solutions.

Issues

  • MLlib architecture

  • Distributed Machine Learning

  • Classification and regression algorithms

  • Clustering techniques

  • Recommendation systems

  • Text processing

  • Optimization of models

  • Pipeline Management

  • Model Deployment

  • Monitoring and updating models

This training is part of the path:

Benefits

  • Acquire advanced knowledge in large-scale machine learning implementation
  • Gain practical skills in designing and optimizing ML models
  • Techniques for effective implementation of ML solutions in a production environment
  • Assimilate methods for monitoring and updating machine learning models
  • ML pipelines management
  • Develop distributed computing skills for ML

Who is this training for?

Data Scientists working with large data sets
ML engineers implementing scalable solutions
AI/ML solution architects
Analytics application developers
Big Data specialists interested in ML
Data analysts expanding into ML

Prerequisites

  • Knowledge of the basics of machine learning
  • Experience in Python or Scala programming
  • Basic knowledge of Apache Spark
  • Knowledge of statistics and mathematics

Training program

01

MLlib architecture

  • Preparing data for learning
02

Basic ML algorithms

  • Distributed Computing in ML
  • Advanced algorithms and models
  • Classification and regression
  • Clustering and dimensionality reduction
  • Recommendation systems
  • Word processing and NLP
  • Optimization and tuning of models
03

Cross-validation

  • Hyperparameter tuning
  • Quality assessment of models
04

Pipeline optimization

  • Implementation and maintenance
  • Deployment of ML models
  • Monitoring and updating models
05

Version management

  • ML Pipeline Management

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 Apache Spark MLlib - large-scale machine learning training for?

This training is designed for professionals looking to develop skills in apache spark mllib - large-scale machine learning. Required level: advanced.

How long is the Apache Spark MLlib - large-scale machine learning training?

The training lasts 5. 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.

Patrycja Petkowska
Patrycja Petkowska 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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Contact us - we'll prepare an offer tailored to your organization's needs.

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