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Releases: paulovn/ml-vm-notebook

UNED 2024

16 Mar 15:00
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  • Python 3.10.12 with a Data Science stack
  • R 4.3
  • Jupyter Notebook with Python & R kernels
  • Optional provisioning for additional packages
  • Patched causalimpact package
  • Based on Ubuntu 22.04

UAM v. 3.2 (Spark 3.4.1)

12 Oct 20:57
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  • Ubuntu 22.04 with Python 3.10 & R 4.3
  • Spark 3.4.1
  • Configuration for GraphFrames 0.8.3
  • Jupyter Notebook with Python 3, Pyspark, Scala & R kernels
  • Optional provisioning for a number of packages

UNED 2023

19 Mar 20:59
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  • Python 3.10.6 with a scientific stack
  • R 4.2
  • Jupyter Notebook with Python & R kernels
  • Optional provisioning for additional packages
  • Based on Ubuntu 22.04

UNED 2022

18 Mar 21:35
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  • Python 3.8.10 with a scientific stack
  • R 4.1.3
  • Jupyter Notebook with Python & R kernels
  • Optional provisioning for additional packages
  • Based on Ubuntu 20.04

UAM v. 3.1 (Spark 3.1.2)

19 Nov 22:21
610df9f
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  • Ubuntu 20.04 with Python 3.8.5 & R 4.0.3
  • Spark 3.1.2
  • Configuration for GraphFrames 0.8.2
  • Jupyter Notebook with Python 3, Pyspark, Scala & R kernels
  • Optional provisioning for a number of packages

CESTE v. 1.0

03 Oct 16:20
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  • Spark 3.1.2
  • Optional provisionings for
    • Hadoop
    • ELK
    • noSQL
    • Kafka (& Kafdrop)

UNED 2021

21 Mar 23:22
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  • Python 3.8.5 with a scientific stack
  • R 4.0.3
  • Jupyter Notebook with Python & R kernels
  • Optional provisioning for additional packages
  • Based on Ubuntu 20.04

UAM v2.5.1 (Spark 2.4.6)

13 Jan 16:49
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Bugfix over 2.5

  • activate NAT DNS resolver, to help in VPN settings
  • default is 2 CPUs
  • fix R configfile creation

UAM v2.5 (Spark 2.4.6)

19 Jun 23:11
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  • Apache Spark 2.4.6
  • Configuration for GraphFrames 0.8.0
  • Python 3.6.7 with a scientific stack
  • R 3.6.2 & RStudio
  • Jupyter Notebook with Python 3, Pyspark, Scala & R kernels
  • Optional provisioning for a number of packages

DatAcademy - NLP

08 Jul 06:23
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  • Python 3.6 (plain Python, with additional libraries such as NumPy, SciPy, Pandas, Matplotlib, Scikit-learn, etc),
  • Pyspark (Python 3.6 + libraries + Spark),
  • Scala 2.11 + Spark
  • R (with SparkR available, though not loaded by default).
  • NLP libraries and tools
  • DL libraries (Tensorflow, PyTorch, Keras)