206 подписчиков
38 видео
01. Python for machine learning introduction
07. Python for machine learning: keras & sentiment classification of IMDB reviews
120 worker and atools: atools tuning
MobaXTerm intro
100 git: conclusions and references
012572 012572 FORTRAN v2 Ondertitels
060 git: multi user scenario
100 worker and atools: atools features
050 git: single user scenario terminal demo
150 worker and atools: conclusions
010 git: introduction
080 worker and atools: worker tuning
070 git: multi user scenario demo
060 worker and atools: worker features
020 git: repository hosting
070 worker and atools: parameter weaver
090 worker and atools: atools parameter exploration
140 worker and atools: file I/O
110 worker and atools: atools demo
090 git: contributing
080 git: details
160 worker and atools: implementation
Command line argument handling
03. Python for machine learning scikit learning: classification clustering with scikit-learn
Create R containers
130 worker and atools: comparison
030 git: SmartGit first push
040 git: single user scenario
050 worker and atools: worker mapreduce
