ABOUT THE AUTHOR

Mariusz Budziński

Data Scientist

Mariusz works at CodiLime as a Data Scientist. His past projects have focused on time series analysis and he is a co-author of a recent patent application based on the use of Meta-learning in time series analysis. His main challenge is to provide advanced AI/ML models for network applications. In his free time, he enjoys cooking and sports.

Mariusz Budziński

Recent posts by Mariusz:

Thumbnail of an article about How to use convolutional networks for time series classification?
DATA

How to use convolutional networks for time series classification?

In this blog post, we would like to address the topic of time series classification. This continues our consideration of the practical use of time series in the domain of networks and cloud infrastructure. In this article we focus on a use case related to distinguishing resource consumption characteristics (e.g. CPU, memory) for different workloads in a computing cluster.
Multiple authors

Multiple authors

Thumbnail of an article about Long-term time series forecasting: an insight into the methods
NETWORKS
DATA

Long-term time series forecasting: an insight into the methods

In this article, we describe the use case and reasoning for long-term traffic forecasting, next we focus on the methods we used, and discuss alternative approaches and challenges to overcome.
Mariusz Budziński

Mariusz Budziński

Thumbnail of an article about Introduction to time series for machine learning
NETWORKS
DATA

Introduction to time series for machine learning

Data is becoming an integral part of everyday life. Even if we are not fully aware of it, we deal with it all the time and it affects our lives in significant ways. This blog post elaborates on a particular type of data: time series. If you want to know more and discover what problems you can solve with time series analysis, you've come to the right place. Have you ever wondered how much data is created (including newly generated, captured, copied, or consumed data) each day? Currently it is 0.33 zettabytes every day!
Mariusz Budziński

Mariusz Budziński

Thumbnail of an article about AI and Machine Learning landscape for networks [infographic]
NETWORKS
DATA

AI and Machine Learning landscape for networks [infographic]

Aritifical intelligence (AI) and machine learning (ML) is a trending topic in all technological domains. It offers a rich set of methods for data processing that can be used to solve practical problems, including those occurring in networks. In this article we present a set of network issues for which the use of ML methods and different AI types can bring benefits and generally seems to make sense. Please note that this is a non-exhaustive list and is open to additions. For greater clarity, five main categories have been used.
Multiple authors

Multiple authors

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