Projects with this topic
-
OpenML dataset: position-sizing-pip-value-by-lot-size https://www.openml.org/d/47313
Updated -
OpenML dataset: position-sizing-losing-streak-equity https://www.openml.org/d/47314
Updated -
OpenML dataset: position-sizing-contract-specifications https://www.openml.org/d/47316
Updated -
OpenML dataset: position-sizing-drawdown-recovery https://www.openml.org/d/47315
Updated -
Personal training enablement templates and survey analysis script. Sample data only.
Updated -
Personal community playbook: onboarding, moderation, content calendar, engagement metrics, events. Sample data only.
Updated -
-
Important Insights--
After analyzing, 61.5% graduated, 20.7% were enrolled, and 17.8% dropped out, showing graduation as the dominant outcome. Students with low grades in the 1st and 2nd semesters showed a very high dropout likelihood close to 71% , confirming early academic performance as a strong dropout indicator. Younger students (18–20 years) achieved better academic results and had lower dropout rates more that 15%. Dropout risk increased steadily with age, exceeding 50% for students aged 29–31, highlighting age as a critical risk factor. 87% of dropouts did not receive scholarships, indicating financial instability as a major contributor to dropout.Updated -
test123=123 test:test123 dataset openml datagit tabular parquet CSV Python JavaScript Java Docker HTML CSS Linux React PHP C++ TypeScript Android game Rust Go GitLab C Ansible API Bash python3 C# nodejs website web golang hacktoberfest Django bot Terraform dotfiles Kubernetes Angular MySQL cli Node.js Kotlin Laravel library Git Amazon Web S... PostgreSQL Windows Unity JSON WordPress Archived shishifubing js devops Ruby plugin shell MongoDB template bootstrap security AI discord automation html5 Spring Qt arduino blog documentation Vue.js Program LaTeX theme gui REST API machine lear... Express legend app ci vue Markdown flask node server docker-compose spring boot Flutter Lua debian in preparation iOS hugo vim R CSS3 minecraft trololoUpdated
-
CRESTA (CRosstabulation to Exchangeable STAtistical data) is an end-to-end Python pipeline developed by Nano - BPS-Statistics Indonesia to automate the transformation of crosstabulations into exchangeable statistical data. It combines deterministic profiling, configurable AI-assisted classification, and a knowledge base of cross-domain codelists to support systematic reuse and governance of statistical concepts and codes.
Updated -
Enterprise IT Infrastructure Services and agile IT infrastructure solutions by RSG Global. We specialize in enterprise IT infrastructure, multi-site infrastructure management services, cloud infrastructure services, and hybrid IT consulting. Our field engineers and technical consultants deploy resilient data protection services, automated disaster recovery services, robust database management services, and business continuity services engineered for modern enterprises.
Updated -
-
-
OpenML dataset: Botanical_Growth_and_Performance_Logs_for_30_Plus_Flora_Species https://www.openml.org/d/47308
Updated -
OpenML dataset: LiTrue-Battery-Engineering-Specs https://www.openml.org/d/47312
Updated -
OpenML dataset: test_oo https://www.openml.org/d/47293
Updated -
OpenML dataset: Residential_Mobility_and_Kinship_Network_Size_Radaris_Anonymized https://www.openml.org/d/47277
Updated -
OpenML dataset: AmesHousing_Analitica_Kag https://www.openml.org/d/47284
Updated -
OpenML dataset: Turkish-EV-Charging-Intent-Dataset https://www.openml.org/d/47280
Updated -
OpenML dataset: medicaid-dental-paid-by-state-2018-2024 https://www.openml.org/d/47287
Updated