Python fundamentals, data structures, OOP, and data science libraries (Pandas, NumPy). Use when writing Python code, data manipulation, or algorithm implementation.
原文の言語: 英語
メニュー
SkillsMP は pluginagentmarketplace/custom-plugin-ai-data-scientist から 12 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
収集済み skill 12 件中 12 件を表示しています。
Python fundamentals, data structures, OOP, and data science libraries (Pandas, NumPy). Use when writing Python code, data manipulation, or algorithm implementation.
原文の言語: 英語
Q-learning, DQN, PPO, A3C, policy gradient methods, multi-agent systems, and Gym environments. Use for training agents, game AI, robotics, or decision-making systems.
原文の言語: 英語
ARIMA, SARIMA, Prophet, trend analysis, seasonality detection, anomaly detection, and forecasting methods. Use for time-based predictions, demand forecasting, or temporal pattern analysis.
原文の言語: 英語
Probability, distributions, hypothesis testing, and statistical inference. Use for A/B testing, experimental design, or statistical validation.
原文の言語: 英語
Image processing, object detection, segmentation, and vision models. Use for image classification, object detection, or visual analysis tasks.
原文の言語: 英語
ETL pipelines, Apache Spark, data warehousing, and big data processing. Use for building data pipelines, processing large datasets, or data infrastructure.
原文の言語: 英語
EDA, dashboards, Matplotlib, Seaborn, Plotly, and BI tools. Use for creating visualizations, exploratory analysis, or dashboards.
原文の言語: 英語
Neural networks, CNNs, RNNs, Transformers with TensorFlow and PyTorch. Use for image classification, NLP, sequence modeling, or complex pattern recognition.
原文の言語: 英語
Supervised/unsupervised learning, model selection, evaluation, and scikit-learn. Use for building classification, regression, or clustering models.
原文の言語: 英語
Docker, Kubernetes, CI/CD, model monitoring, and cloud platforms. Use for deploying ML models to production, setting up pipelines, or infrastructure.
原文の言語: 英語
Quantization, pruning, AutoML, hyperparameter tuning, and performance optimization. Use for improving model performance, reducing size, or automated ML.
原文の言語: 英語
Text processing, sentiment analysis, LLMs, and NLP frameworks. Use for text classification, named entity recognition, or language models.
原文の言語: 英語