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Maqa3333

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active 2026-02-19 → 2026-07-08 (UTC) · 42 repositories

Complete coverage27,150 / 27,152 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-09-19 (UTC)
Events
49
Pushes
22
Pull requests
14
Issues
0
Reviews
0
Repositories
42

Activity over time

Daily event counts in the loaded window

Line chart, 140 days from 2026-02-19 to 2026-07-08. Pushes: 22 total, peak 1 in a day. Pull requests: 14 total, peak 2 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

RepositoryContributionsPushesPRsIssuesCommentsLast seen
Maqa3333/m8-05-assessment220002026-06-24
Data-AI-IDDA/m3-05-lab-bootstrap-cis-practice101002026-04-02
Data-AI-IDDA/m2-01-lab-data-sources-representation101002026-03-03
Data-AI-IDDA/m3-09-lab-feature-relationship-diagnostics101002026-04-08
Data-AI-IDDA/m3-13-assessment101002026-04-12
Data-AI-IDDA/m4-04-lab-ensemble-methods101002026-04-26
Data-AI-IDDA/m6-04-assessment101002026-05-22
Data-AI-IDDA/m6-09-assessment101002026-05-31
Maqa3333/m1-01-lab-ipython-python-basics110002026-02-19
Data-AI-IDDA/m1-06-lab-loading-cleaning101002026-02-25
Maqa3333/m4-06-lab-unsupervised-learning110002026-05-12
Maqa3333/m2-01-lab-data-sources-representation110002026-03-03
Maqa3333/m7-04-lab-fastapi-ml-serving110002026-06-10
Data-AI-IDDA/m6-07-lab-transfer-learning-fine-tuning101002026-06-01
Maqa3333/m1-09-assessment110002026-03-01
Maqa3333/m6-07-lab-transfer-learning-fine-tuning110002026-06-01
Data-AI-IDDA/m3-02-lab-simulation-first-probability101002026-03-31
Maqa3333/m3-05-lab-bootstrap-cis-practice110002026-04-02
Maqa3333/m4-04-lab-ensemble-methods110002026-04-26
Maqa3333/m8-01-lab-from-transformers-to-llms110002026-06-17
Maqa3333/m9-05-lab-llm-workflows-mcp110002026-07-03
Maqa3333/m7-02-lab-mlops-lifecycle-reproducibility110002026-06-05
Maqa3333/m4-08-lab-model-training-evaluation110002026-05-13
Maqa3333/m6-04-assessment110002026-05-22
Maqa3333/m6-09-assessment110002026-05-31
Maqa3333/m4-01-lab-fundamentals-feature-engineering110002026-04-20
Maqa3333/m4-10-assessment110002026-05-10
Maqa3333/m9-07-lab-multi-agent-orchestration-safety110002026-07-08
Data-AI-IDDA/m1-08-lab-viz-time-series-advanced-modeling101002026-02-27
Maqa3333/m1-02-lab-data-structures-functions110002026-02-20
Data-AI-IDDA/m4-03-lab-classification101002026-04-26
Maqa3333/m6-03-lab-convolutional-neural-networks110002026-05-25
Data-AI-IDDA/m2-08-lab-practical-data-pipelines101002026-03-15
Maqa3333/m2-04-lab-etl-workflows-dataflow110002026-03-08
Data-AI-IDDA/m3-06-lab-t-tests-assumption-checks101002026-04-05
Data-AI-IDDA/m1-02-lab-data-structures-functions000002026-02-20
Data-AI-IDDA/m6-01-lab-neural-networks-fundamentals000002026-05-18
Data-AI-IDDA/m3-03-lab-bias-clinic-sampling-variability000002026-04-02
Data-AI-IDDA/m8-04-lab-adapting-trusting-llms000002026-06-22
Data-AI-IDDA/m6-08-lab-model-conversions-inferencing000002026-06-01
Data-AI-IDDA/m1-03-lab-numpy-arrays-and-advanced-operations000002026-02-19
Data-AI-IDDA/m1-09-assessment000002026-02-27

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
nigarrustamova5
Data-AI-IDDA/m1-08-lab-viz-time-series-advanced-modelingData-AI-IDDA/m3-09-lab-feature-relationship-diagnosticsData-AI-IDDA/m3-06-lab-t-tests-assumption-checksData-AI-IDDA/m6-07-lab-transfer-learning-fine-tuning+1
royanasirova5
Data-AI-IDDA/m3-09-lab-feature-relationship-diagnosticsData-AI-IDDA/m4-03-lab-classificationData-AI-IDDA/m2-01-lab-data-sources-representationData-AI-IDDA/m4-04-lab-ensemble-methods+1
khavar-analytics4
Data-AI-IDDA/m4-04-lab-ensemble-methodsData-AI-IDDA/m4-03-lab-classificationData-AI-IDDA/m3-05-lab-bootstrap-cis-practiceData-AI-IDDA/m6-07-lab-transfer-learning-fine-tuning
wiajane4
Data-AI-IDDA/m1-08-lab-viz-time-series-advanced-modelingData-AI-IDDA/m2-08-lab-practical-data-pipelinesData-AI-IDDA/m2-01-lab-data-sources-representationData-AI-IDDA/m1-06-lab-loading-cleaning
AyxanMuxtar3
Data-AI-IDDA/m3-13-assessmentData-AI-IDDA/m6-09-assessmentData-AI-IDDA/m3-05-lab-bootstrap-cis-practice
Jabrail-Atakishiyev3
Data-AI-IDDA/m6-04-assessmentData-AI-IDDA/m2-01-lab-data-sources-representationData-AI-IDDA/m1-06-lab-loading-cleaning
apoplavsky3
Data-AI-IDDA/m3-02-lab-simulation-first-probabilityData-AI-IDDA/m3-13-assessmentData-AI-IDDA/m6-07-lab-transfer-learning-fine-tuning
d1nsrz3
Data-AI-IDDA/m6-04-assessmentData-AI-IDDA/m3-13-assessmentData-AI-IDDA/m1-06-lab-loading-cleaning
esliehmedova3
Data-AI-IDDA/m2-08-lab-practical-data-pipelinesData-AI-IDDA/m3-09-lab-feature-relationship-diagnosticsData-AI-IDDA/m3-13-assessment
nargizaliyeva233
Data-AI-IDDA/m3-02-lab-simulation-first-probabilityData-AI-IDDA/m2-08-lab-practical-data-pipelinesData-AI-IDDA/m1-06-lab-loading-cleaning
AysuAnar2
Data-AI-IDDA/m1-08-lab-viz-time-series-advanced-modelingData-AI-IDDA/m4-03-lab-classification
ElvinNasirov2
Data-AI-IDDA/m6-09-assessmentData-AI-IDDA/m3-05-lab-bootstrap-cis-practice
NarminDirayeva2
Data-AI-IDDA/m1-08-lab-viz-time-series-advanced-modelingData-AI-IDDA/m3-13-assessment
Revan-shift2
Data-AI-IDDA/m3-09-lab-feature-relationship-diagnosticsData-AI-IDDA/m3-05-lab-bootstrap-cis-practice
ShamilAliyew2
Data-AI-IDDA/m2-08-lab-practical-data-pipelinesData-AI-IDDA/m2-01-lab-data-sources-representation
ZarifaMusayeva2
Data-AI-IDDA/m6-09-assessmentData-AI-IDDA/m1-06-lab-loading-cleaning
adilhasanov-glitch2
Data-AI-IDDA/m1-06-lab-loading-cleaningData-AI-IDDA/m3-05-lab-bootstrap-cis-practice
ilahes2
Data-AI-IDDA/m2-08-lab-practical-data-pipelinesData-AI-IDDA/m6-07-lab-transfer-learning-fine-tuning
jannatsamadov2
Data-AI-IDDA/m2-08-lab-practical-data-pipelinesData-AI-IDDA/m3-13-assessment
orxannuriyev2
Data-AI-IDDA/m4-04-lab-ensemble-methodsData-AI-IDDA/m3-09-lab-feature-relationship-diagnostics
seljankhasiyeva2
Data-AI-IDDA/m3-06-lab-t-tests-assumption-checksData-AI-IDDA/m3-09-lab-feature-relationship-diagnostics
AliAgabalayev1
Data-AI-IDDA/m3-13-assessment
KamalMusayev1
Data-AI-IDDA/m1-06-lab-loading-cleaning
Manheim6661
Data-AI-IDDA/m1-06-lab-loading-cleaning
SamaAmrullayeva1
Data-AI-IDDA/m3-13-assessment

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