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Machine Learning for Big Data

The aim of this course is to present an overview of tools and concepts from machine learning on big data.
Level
Designed for participants with basic knowledge and experience
intermediate
Course length
1 day
Language
 cz  eu
Course code
KT21010290
Machine learning
Category:
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Courses on a specific date with a live lecturer

Term
Language
Place
Form
?
How and where the course takes place.
Price without VAT
Open term
?
We will agree on a specific date together. This is a non-binding order.
Language
Place
Praha
Form
classroom
?
The course with an instructor in classroom.
Code of the course: KT21010290-0002
Price without VAT
4 990 Kč
Open term
?
We will agree on a specific date together. This is a non-binding order.
Language
Place
Praha
Form
classroom
?
The course with an instructor in classroom.
Code of the course: KT21010290-0003
Price without VAT
4 990 Kč

Course description

After going through the course participants should be able to tell what is the right tool to use for the given problem, whether there is a simpler solution and how to avoid common mistakes. Special attention will be given to Spark as a universal tool that can be used for both big data processing and machine learning.

Required knowledge

  • Basics of Python and working in Google Colab
  • Basics of machine learning on the level of our course Introduction to machine Learning

Course content

  • Overview of Big Data concepts and tools
    • From small to big data and estimating its value
    • Row vs column-oriented database
    • HDFS (Hadoop Distributed File System)
    • Big data file formats – Parquet, ORC, Avro
    • Compression – gzip, snappy, zstd
    • SQL databases – BigQuery, Redshift, Clickhouse, Snowflake, Vertica
  • A practical example of big data value proposition
  • Introduction to Spark
    • MapReduce
    • Spark Computing Engine and RDDs (Resilient Distributed Datasets)
    • DataFrames
    • Spark Ecosystem
    • Most common Spark mistakes
    • How to run Spark
    • Alternatives – Apache Beam (Dataflow), Dask, lambdas
  • A practical example with Spark
  • ML strategies for Big Data
    • Incremental learning
    • Batch learning for neural networks
    • Distributed training
    • Federated learning
    • Alternative strategies
      • Random sampling
      • Submodels
      • Larger workstation
  • Frameworks
    • Scikit-learn with partial_fit
    • MLlib
    • Dask-ML
  • Practical examples with various frameworks
  • Common mistakes

Lecturers

Mojmír Vinkler
Mojmír Vinkler

He first started working with data ten years ago, during which he was involved in the development of ML projects from their design, through implementation to value creation, in various industries such as healthcare, fintech or marketing. He currently works as an ML engineer as a US consultant for startups.  

Do you want this tailor-made course for your company?

Contact us

News with the course

Náhledový obrázek novinky
Machine Learning 18. 3. 2023
The differences between Machine learning and Artificiant inteligence

Machine learning (ML) and Artificial intelligence (AI) are related fields, but they are not the same thing. AI is a broader field that encompasses many different technologies, including machine learning. Check with us the key differences between machine learning and artificial intelligence.

Náhledový obrázek novinky
Machine Learning 3. 6. 2021
Discover the benefits of Machine Learning

Machine Learning allows companies to be efficient, search for patterns in data, automate and make decisions with minimal human intervention. Learned algorithms solve defined tasks in real time and based on input data. At the same time, they learn from the new data and adapt to changing conditions.

Previous courses

Do you want this tailor-made course for your company?

Contact us

News with the course

Náhledový obrázek novinky
Machine Learning 18. 3. 2023
The differences between Machine learning and Artificiant inteligence

Machine learning (ML) and Artificial intelligence (AI) are related fields, but they are not the same thing. AI is a broader field that encompasses many different technologies, including machine learning. Check with us the key differences between machine learning and artificial intelligence.

Náhledový obrázek novinky
Machine Learning 3. 6. 2021
Discover the benefits of Machine Learning

Machine Learning allows companies to be efficient, search for patterns in data, automate and make decisions with minimal human intervention. Learned algorithms solve defined tasks in real time and based on input data. At the same time, they learn from the new data and adapt to changing conditions.

Why with us