Philipp Drieger

Philipp Drieger

Deutschland
3852 Follower:innen 500+ Kontakte

Anmelden, um das Profil zu sehen

Info

Philipp Drieger works as Global Principal Machine Learning Architect at Splunk. Over the…

Artikel von Philipp Drieger

Aktivitäten

Anmelden, um alle Aktivitäten zu sehen

Berufserfahrung

  • Splunk Grafik

    Splunk

    Greater Munich Metropolitan Area

  • -

    Munich Area, Germany

  • -

    Munich Area, Germany

  • -

  • -

  • -

Ausbildung

Bescheinigungen und Zertifikate

Veröffentlichungen

  • Semantic Network Analysis as a Method for Visual Text Analytics

    Procedia – Social and Behavioral Sciences, Volume 79, 6 June 2013, Manuel Fischer (Ed.), Elsevier, pp. 4–17. 9th Conference on Applications of Social Network Analysis (ASNA) 2012

    This paper proposes an approach on a method for visual text analytics to support knowledge building, analytical reasoning and explorative analysis. For this purpose we use semantic network models that are automatically retrieved from unstructured text data using a parametric k-next-neighborhood model. Semantic networks are analyzed with methods of network analysis to gain quantitative and qualitative insights. Quantitative metrics can support the qualitative analysis and exploration of semantic…

    This paper proposes an approach on a method for visual text analytics to support knowledge building, analytical reasoning and explorative analysis. For this purpose we use semantic network models that are automatically retrieved from unstructured text data using a parametric k-next-neighborhood model. Semantic networks are analyzed with methods of network analysis to gain quantitative and qualitative insights. Quantitative metrics can support the qualitative analysis and exploration of semantic structures. We discuss theoretical presuppositions regarding the text modeling with semantic networks to provide a basis for subsequent semantic network analysis. By presenting a systematic overview of basic network elements and their qualitative meaning for semantic network analysis, we describe exploration strategies that can support analysts to make sense of a given network. As a proof of concept, we illustrate the proposed method by an exemplary analysis of a wikipedia article using a visual text analytics system that leverages semantic network visualization for exploration and analysis.

    Veröffentlichung anzeigen

  • Visual text analytics using semantic networks and interactive 3d visualization

    EuroVA 2012: International Workshop on Visual Analytics (Vienna, Austria, 2012), K. Matkovic and G. Santucci (Eds.), Eurographics Association, pp. 43–47

Patente

  • Providing machine learning models for classifying domain names for malware detection

    Ausgestellt am US11843622B1

    Techniques are described for providing users of a data intake and query system with pre-trained ML models capable of identifying malicious threats (e.g., malware, botnets, ransomware, etc.) in users' computing environments based on an analysis of Domain Name System (DNS) log data collected from DNS servers in users' environments. DNS log data is ingested by a data intake and query system and processed to obtain searchable timestamped event data. This event data can then be used as input to ML…

    Techniques are described for providing users of a data intake and query system with pre-trained ML models capable of identifying malicious threats (e.g., malware, botnets, ransomware, etc.) in users' computing environments based on an analysis of Domain Name System (DNS) log data collected from DNS servers in users' environments. DNS log data is ingested by a data intake and query system and processed to obtain searchable timestamped event data. This event data can then be used as input to ML models provided by a security ML application described herein to detect potential occurrences of malicious activity within users' computing environments.

    Andere Erfinder:innen
    Patent anzeigen

Projekte

  • Splunk App for Data Science and Deep Learning

    The Deep Learning Toolkit for Splunk allows you to integrate advanced custom machine learning systems with the Splunk platform. It extends Splunk’s Machine Learning Toolkit with prebuilt Docker containers for TensorFlow, PyTorch and a collection of NLP and classical machine learning libraries. By using predefined workflows for rapid development with Jupyter Lab Notebooks the app enables you to build, test (e.g. using TensorBoard) and operationalise your customised models with Splunk. You can…

    The Deep Learning Toolkit for Splunk allows you to integrate advanced custom machine learning systems with the Splunk platform. It extends Splunk’s Machine Learning Toolkit with prebuilt Docker containers for TensorFlow, PyTorch and a collection of NLP and classical machine learning libraries. By using predefined workflows for rapid development with Jupyter Lab Notebooks the app enables you to build, test (e.g. using TensorBoard) and operationalise your customised models with Splunk. You can leverage GPUs for compute intense training tasks and flexibly deploy models on CPU or GPU enabled containers. The app ships with various examples that showcase different deep learning and machine learning algorithms for classification, regression, forecasting, clustering, graph analytics and NLP. This allows you to tackle advanced data science use cases in Splunk’s main areas of IT Operations, Security, Application Development, IoT, Business Analytics and beyond.

    Projekt anzeigen

  • NVIDIA GPU Computing: 2 Million Pixel Experiment

    This CUDA experiment maps a FULL-HD (1920x1080 @ 30 frames per second, MPEG2 compression) video source into 3D space. Each frame is processed in real-time on the GPU using CUDA. Each pixel in a frame (2.073.600 pixels per frame) is scaled by its luminance value and given the original color. The camera flight is realized with a 3D space navigator in real-time. This application is written in C# using DirectX 11, CUDA.NET and DirectShow.NET libraries. Benchmarks: GPU load is about 85% (GTX 260)…

    This CUDA experiment maps a FULL-HD (1920x1080 @ 30 frames per second, MPEG2 compression) video source into 3D space. Each frame is processed in real-time on the GPU using CUDA. Each pixel in a frame (2.073.600 pixels per frame) is scaled by its luminance value and given the original color. The camera flight is realized with a 3D space navigator in real-time. This application is written in C# using DirectX 11, CUDA.NET and DirectShow.NET libraries. Benchmarks: GPU load is about 85% (GTX 260), GPU memory controller load 25%, CPU (i7-920) is at 20%.

    Projekt anzeigen

  • 3D Graph Network Topology Visualization

    –

    Graph Algorithms for Splunk’s Machine Learning Toolkit and custom visualisation for Splunk to plot relationships between objects with force directed graph based on ThreeJS/WebGL.

    Find more information on the details page with link to blog articles like:
    https://www.splunk.com/en_us/blog/machine-learning/chasing-a-hidden-gem-graph-analytics-with-splunk-s-machine-learning-toolkit.html

    Projekt anzeigen

  • DGA App for Splunk

    –

    This Splunk app shows how to Operationalize Machine Learning using MLTK to detect malicious domain names. Malware like Botnets use domain generation algorithms (DGAs) to create URLs that host malicious websites or command and control servers. Static matching does not always help, so machine learning models can add value and allow to increase detection rates.

    Projekt anzeigen

Auszeichnungen/Preise

  • Innovation Award FY19

    Splunk Inc.

  • Global Team Work Award FY18

    Splunk Inc.

  • Intel Perceptual Computing Challenge 2013

    Intel Corp.

    2nd prize Winner "Open Innovation"

Erhaltene Empfehlungen

1 Person hat Philipp Drieger empfohlen

Jetzt anmelden und ansehen

Weitere Aktivitäten von Philipp Drieger

Philipp Driegers vollständiges Profil ansehen

  • Herausfinden, welche gemeinsamen Kontakte Sie haben
  • Sich vorstellen lassen
  • Philipp Drieger direkt kontaktieren
Mitglied werden. um das vollständige Profil zu sehen

Weitere ähnliche Profile

Weitere Beiträge entdecken

Entwickeln Sie mit diesen Kursen neue Kenntnisse und Fähigkeiten

Alle Kurse anzeigen