go-concurrency
Go concurrency patterns - goroutines, channels, sync primitives
Découvrez les skills Documentation, comparez leurs dépôts et consultez leurs instructions.
Go concurrency patterns - goroutines, channels, sync primitives
Go modules and dependency management
CLI application patterns and best practices
LLMs, prompt engineering, RAG systems, LangChain, and AI application development
Docker, Kubernetes, container orchestration, and cloud-native deployment for data applications
FastAPI, REST APIs, GraphQL, data service design, and API best practices
Data pipeline architecture, ETL/ELT patterns, data modeling, and production data platform design
Snowflake, BigQuery, Redshift, dimensional modeling, and modern data warehouse architecture
Terraform, Pulumi, CloudFormation, and infrastructure as code for data platforms
Master Python fundamentals, OOP, data structures, async programming, and production-grade scripting for data engineering
Prometheus, Grafana, logging, alerting, and data pipeline observability
Portfolio building, technical interviews, job search strategies, and continuous learning
pytest, data validation, Great Expectations, and quality assurance for data systems
Supervised & unsupervised learning, scikit-learn, XGBoost, model evaluation, feature engineering for production ML
SQL query optimization, schema design, indexing strategies, and relational database mastery for production data systems
MongoDB, Redis, Cassandra, DynamoDB, and distributed database patterns for scalable applications
MLflow, model versioning, experiment tracking, model registry, and production ML systems
Apache Airflow, dbt, Prefect, Dagster, and modern data orchestration for production data pipelines
GitHub Actions, GitLab CI, Jenkins, and automated deployment pipelines
Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads
AWS, GCP, Azure data platforms, infrastructure as code, and cloud-native data solutions
Git workflows, branching strategies, collaboration, and code management
PyTorch, TensorFlow, neural networks, CNNs, transformers, and deep learning for production
Write Arcade expressions for dynamic calculations in popups, renderers, labels, and field calculations. Use for data-driven styling, custom labels, and computed fields.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.