「e-learning」の検索結果

Selects informative features for biomarker discovery using Boruta all-relevant selection, mRMR minimum redundancy, and LASSO regularization. Use when identifying biomarkers from high-dimensional omics data.

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Analyzes time-to-event data using Kaplan-Meier curves, log-rank tests, and Cox proportional hazards regression with lifelines. Builds survival models from clinical and omics features. Use when predicting patient survival or modeling time-to-event outcomes.

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Workflow for predictive modeling, biomarker discovery, survival modeling, and explainability over omics-derived features.

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ClearML is an open-source MLOps platform that records machine-learning experiments, versions datasets, chains tasks into pipelines and runs them on remote machines through agents and queues. Use when a user asks to "track experiments with ClearML", "log metrics, artifacts and models", "version a dataset", "run training on a remote GPU with clearml-agent", "build a ClearML pipeline", "run hyperparameter optimization", or "self-host ClearML Server". Covers the clearml 2.x Python SDK, clearml-agent 3.x and ClearML Server 2.x.

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AI自适应学习 (AI Adaptive Learning) Master OS — automated mastery of AI Adaptive Learning: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on AI Adaptive Learning problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「自适应学习」「智能诊断」「自适应题库」「学习路径规划」「知识追踪」

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Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus

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Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus

日本語の概要は準備中です。原文の説明を表示しています。

Design a worked example fading sequence from fully worked examples through to independent practice. Use when teaching procedures, algorithms, or multi-step processes to novice learners.

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Present project-design pathway options and orchestrate regenerative projects using backwards design, PBL, SEEDS, compassionate systems action, or civic/service pathways.

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Define the scope and purpose of a complex inquiry before mapping or futures work begins. Use when a class or group needs to agree what they are investigating, who it matters to, and at what scale.

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Design a pedagogical documentation protocol for making children's learning processes visible and shareable. Use when documenting learning, communicating with families, or planning next steps.

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Design a learning task where mixed-age students work together with mutual benefit for all age groups. Use when planning cross-age tutoring, vertical grouping, or multi-year group activities.

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Create an interactive digital worked example sequence with fading for online or blended delivery. Use when building e-learning modules, LMS content, or app-based instruction.

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Structure a direct experience into a full learning cycle with concrete experience, reflection, and conceptual transfer. Use when planning field trips, simulations, or practical tasks.

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Meta-cognitive and practical strategies for learning any language -- learner autonomy, goal setting, strategy taxonomy (Oxford's SILL framework), memory strategies, cognitive strategies (note-taking, summarizing, analyzing, reasoning), compensation strategies, metacognitive strategies (planning, monitoring, evaluating), affective strategies (managing anxiety, self-encouragement), social strategies (collaboration, questioning, empathy), immersion design, study habit optimization, plateau diagnosis, and motivation maintenance. Use when designing a language learning plan, diagnosing a learner's stuck points, selecting study methods, or building self-directed learning skills.

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Supervised and unsupervised learning, bias-variance tradeoff, cross-validation, decision trees, ensemble methods, neural network fundamentals, and the practitioner's workflow from problem framing through deployment. Covers classification, regression, clustering, dimensionality reduction, regularization, hyperparameter tuning, and evaluation metrics. Use when building predictive models, selecting algorithms, or understanding the machine learning pipeline.

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Nature-style remote-sensing manuscript reviewer skill for evaluating Earth-observation products, retrievals, machine-learning maps, validation design, uncertainty propagation, spatial transferability and claim-scope calibration.

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Evaluates ML applications in investment with feature engineering, model selection, and implementation considerations for alpha generation. Use when evaluating ML for investing, designing ML pipelines, or assessing ML strategy feasibility.

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Set up systematic data labeling workflows using Label Studio or similar tools. Implement quality controls, measure inter-annotator agreement, manage labeler teams, and integrate labeled data into ML training pipelines. Use when starting a supervised ML project that requires labeled training data, when model performance is limited by insufficient labeled examples, when labeling text, images, audio, or video, or when implementing active learning to prioritize the most valuable examples.

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Use when asked to create a multi-session learning plan. Returns a milestoned plan, practice, and review rubric. Don't use for tasks that require source or remote-system changes.

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Execute and analyze AI Data Poisoning attacks. By subtly injecting malicious or targeted misinformation into an LLM's training or fine-tuning dataset, an attacker can covertly manipulate the model's future outputs, implant backdoors, or enforce biases without altering the model architecture.

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Use when a task needs the judgment of a Biology Professor at a research university — writing or defending an NIH/NSF grant budget, deciding authorship order on a paper, navigating an IACUC or biosafety protocol, mentoring a PhD student through a stalled project, or converting a course when active-learning data doesn't match student pushback.

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Label smarter, not more — pick the most informative examples for annotation to maximize model gains per label.

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Short alias for external-site-profile-learning. Use this when investigating, adding, validating, or debugging external website profiles for the 99idea Playwright browser demo.

日本語の概要は準備中です。原文の説明を表示しています。