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wiserval

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active 2026-02-18 → 2026-06-30 (UTC) · 57 repositories

Complete coverage27,149 / 27,151 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-09-19 (UTC)
Events
65
Pushes
45
Pull requests
10
Issues
0
Reviews
0
Repositories
57

Activity over time

Daily event counts in the loaded window

Line chart, 133 days from 2026-02-18 to 2026-06-30. Pushes: 45 total, peak 3 in a day. Pull requests: 10 total, peak 1 in a day. Issues: 0 total, peak 0 in a day.

  • Pushes
  • Pull requests
  • Issues

Pull requests and issues are under-captured in the later part of this window. GH Archive progressively stopped recording non-push events during 2026 — −95% or worse by the end of the window. A decline in those two series reflects the archive rather than this account. Pushes stay reliable throughout, so read them as the real signal. Data health has the measurements.

Repositories worked on

Ranked by contributions — pushes, PRs, issues, reviews and comments, so stars and forks do not inflate the list · top 50

RepositoryContributionsPushesPRsIssuesCommentsLast seen
wiserval/m6-04-assessment330002026-05-21
wiserval/m9-04-lab-tool-use-function-calling220002026-06-27
wiserval/m6-01-lab-neural-networks-fundamentals220002026-05-12
wiserval/m2-08-lab-practical-data-pipelines220002026-04-10
wiserval/m6-06-lab-deep-reinforcement-learning220002026-05-22
Data-AI-IDDA/m7-02-lab-mlops-lifecycle-reproducibility101002026-05-28
Data-AI-IDDA/m7-05-lab-model-serving-inference-at-scale101002026-06-04
Data-AI-IDDA/m2-08-lab-practical-data-pipelines101002026-03-14
wiserval/m2-02-lab-data-models-storage-engines110002026-03-03
wiserval/m2-01-lab-data-sources-representation110002026-03-02
Data-AI-IDDA/m2-06-lab-datasets-labeling101002026-03-12
Data-AI-IDDA/m9-01-lab-embeddings-vector-search101002026-06-17
Data-AI-IDDA/m1-09-assessment101002026-02-27
Data-AI-IDDA/m4-01-lab-fundamentals-feature-engineering101002026-04-17
wiserval/m2-03-lab-data-formats-execution-engines110002026-03-05
Data-AI-IDDA/m6-08-lab-model-conversions-inferencing101002026-05-23
wiserval/m3-01-lab-eda-toolkit-summary-pitfalls110002026-03-22
wiserval/m3-13-assessment110002026-04-10
wiserval/m4-01-lab-fundamentals-feature-engineering110002026-04-17
wiserval/m3-05-lab-bootstrap-cis-practice110002026-03-31
wiserval/m9-07-lab-multi-agent-orchestration-safety110002026-06-30
wiserval/m3-06-lab-t-tests-assumption-checks110002026-04-01
wiserval/m9-08-assessment110002026-06-27
wiserval/m4-10-assessment110002026-05-08
wiserval/m9-05-lab-llm-workflows-mcp110002026-06-28
wiserval/m6-02-lab-training-deep-networks110002026-05-13
wiserval/m8-01-lab-from-transformers-to-llms110002026-06-08
Data-AI-IDDA/m6-06-lab-deep-reinforcement-learning101002026-05-22
wiserval/m3-08-assessment110002026-04-03
wiserval/m1-05-lab-pandas-foundations110002026-02-23
wiserval/m9-02-lab-rag-system-architecture110002026-06-24
wiserval/m2-07-lab-real-world-data110002026-03-13
wiserval/m7-01-lab-ai-solution-architecture110002026-05-27
wiserval/m6-08-lab-model-conversions-inferencing110002026-05-23
wiserval/m4-09-lab-model-deployment110002026-05-10
Data-AI-IDDA/m1-04-assessment101002026-02-20
wiserval/m1-01-lab-ipython-python-basics110002026-02-18
wiserval/m4-03-lab-classification110002026-04-18
wiserval/m1-02-lab-data-structures-functions110002026-02-18
wiserval/m3-10-lab-group-effects-variance-explained110002026-04-07
wiserval/m3-07-lab-chi-square-power-planning110002026-04-02
wiserval/m6-03-lab-convolutional-neural-networks110002026-05-14
wiserval/m3-12-lab-metric-uncertainty-model-comparison110002026-04-10
wiserval/m2-04-lab-etl-workflows-dataflow110002026-03-07
wiserval/m7-07-assessment110002026-06-07
wiserval/m6-05-lab-sequence-models-transformers110002026-05-22
wiserval/m4-02-lab-regression110002026-04-18
wiserval/m4-04-lab-ensemble-methods110002026-04-16
wiserval/m6-09-assessment110002026-05-31
Data-AI-IDDA/m2-04-lab-etl-workflows-dataflow000002026-03-07

Works with

People who contribute to the same repositories, ranked by how many they share · automation excluded, or every account would appear to work with everyone

ContributorShared reposRepositories in common
ElvinNasirov4
Data-AI-IDDA/m1-04-assessmentData-AI-IDDA/m6-06-lab-deep-reinforcement-learningData-AI-IDDA/m1-09-assessmentData-AI-IDDA/m7-02-lab-mlops-lifecycle-reproducibility
adilhasanov-glitch3
Data-AI-IDDA/m1-04-assessmentData-AI-IDDA/m6-06-lab-deep-reinforcement-learningData-AI-IDDA/m1-09-assessment
apoplavsky3
Data-AI-IDDA/m1-04-assessmentData-AI-IDDA/m1-09-assessmentData-AI-IDDA/m2-06-lab-datasets-labeling
ilahes3
Data-AI-IDDA/m2-08-lab-practical-data-pipelinesData-AI-IDDA/m1-09-assessmentData-AI-IDDA/m7-02-lab-mlops-lifecycle-reproducibility
wiajane3
Data-AI-IDDA/m1-04-assessmentData-AI-IDDA/m6-06-lab-deep-reinforcement-learningData-AI-IDDA/m2-08-lab-practical-data-pipelines
AyxanMuxtar2
Data-AI-IDDA/m6-06-lab-deep-reinforcement-learningData-AI-IDDA/m1-09-assessment
Manheim6662
Data-AI-IDDA/m1-04-assessmentData-AI-IDDA/m7-05-lab-model-serving-inference-at-scale
alexiiiiiiiii2
Data-AI-IDDA/m1-04-assessmentData-AI-IDDA/m2-08-lab-practical-data-pipelines
d1nsrz2
Data-AI-IDDA/m6-08-lab-model-conversions-inferencingData-AI-IDDA/m4-01-lab-fundamentals-feature-engineering
nigarrustamova2
Data-AI-IDDA/m1-04-assessmentData-AI-IDDA/m1-09-assessment
AliAgabalayev1
Data-AI-IDDA/m7-02-lab-mlops-lifecycle-reproducibility
Jabrail-Atakishiyev1
Data-AI-IDDA/m1-09-assessment
Maqa33331
Data-AI-IDDA/m2-08-lab-practical-data-pipelines
NarminDirayeva1
Data-AI-IDDA/m1-04-assessment
Revan-shift1
Data-AI-IDDA/m4-01-lab-fundamentals-feature-engineering
SamaAmrullayeva1
Data-AI-IDDA/m1-09-assessment
ShamilAliyew1
Data-AI-IDDA/m2-08-lab-practical-data-pipelines
ZarifaMusayeva1
Data-AI-IDDA/m1-09-assessment
aliyarlinurana1
Data-AI-IDDA/m1-04-assessment
eliyevaulviye1
Data-AI-IDDA/m7-05-lab-model-serving-inference-at-scale
esliehmedova1
Data-AI-IDDA/m2-08-lab-practical-data-pipelines
jannatsamadov1
Data-AI-IDDA/m2-08-lab-practical-data-pipelines
nargizaliyeva231
Data-AI-IDDA/m2-08-lab-practical-data-pipelines
royanasirova1
Data-AI-IDDA/m6-06-lab-deep-reinforcement-learning

Counts cover only the window loaded into ClickHouse and count events, not this account's lifetime totals on GitHub.