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itsmostafa
GitHub-Creator-Profil

itsmostafa

Repository-Ansicht von 31 gesammelten Skills in 4 GitHub-Repositories.

gesammelte Skills
31
Repositories
4
aktualisiert
2. Sept. 2026
Repository-Explorer

Repositories und repräsentative Skills

ecs
Netzwerk- und Computersystemadministratoren

AWS ECS container orchestration for running Docker containers. Use when deploying containerized applications, configuring task definitions, setting up services, managing clusters, or troubleshooting container issues.

12. Mai 2026
ec2
Netzwerk- und Computersystemadministratoren

AWS EC2 virtual machine management — instances, security groups, key pairs, AMIs, EBS volumes, Auto Scaling Groups, Spot Instances, Session Manager, placement groups, and instance lifecycle automation. Trigger on ANY of these, even when EC2 isn't named…

12. Mai 2026
api-gateway
Softwareentwickler

AWS API Gateway for REST and HTTP API management. Use when creating APIs, configuring integrations, setting up authorization, managing stages, implementing rate limiting, or troubleshooting API issues.

8. Jan. 2026
bedrock
Softwareentwickler

AWS Bedrock foundation models for generative AI. Use when invoking foundation models, building AI applications, creating embeddings, configuring model access, or implementing RAG patterns.

8. Jan. 2026
cloudformation
Softwareentwickler

AWS CloudFormation infrastructure as code for stack management. Use when writing templates, deploying stacks, managing drift, troubleshooting deployments, or organizing infrastructure with nested stacks.

8. Jan. 2026
cloudwatch
Netzwerk- und Computersystemadministratoren

AWS CloudWatch monitoring for logs, metrics, alarms, and dashboards. Use when setting up monitoring, creating alarms, querying logs with Insights, configuring metric filters, building dashboards, or troubleshooting application issues.

8. Jan. 2026
cognito
Softwareentwickler

AWS Cognito user authentication and authorization service. Use when setting up user pools, configuring identity pools, implementing OAuth flows, managing user attributes, or integrating with social identity providers.

8. Jan. 2026
dynamodb
Datenbankarchitekten

AWS DynamoDB NoSQL database for scalable data storage. Use when designing table schemas, writing queries, configuring indexes, managing capacity, implementing single-table design, or troubleshooting performance issues.

8. Jan. 2026
Es werden 8 von 18 gesammelten Skills angezeigt.
agents
Softwareentwickler

Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven tasks.

6. Mai 2026
context-engineering
Softwareentwickler

Strategies for managing LLM context windows effectively in AI agents. Use when building agents that handle long conversations, multi-step tasks, tool orchestration, or need to maintain coherence across extended interactions.

6. Mai 2026
lora
Datenwissenschaftler

Parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). Use when fine-tuning large language models with limited GPU memory, creating task-specific adapters, or when you need to train multiple specialized models from a single base.

6. Mai 2026
mlx
Datenwissenschaftler

Running and fine-tuning LLMs on Apple Silicon with MLX. Use when working with models locally on Mac, converting Hugging Face models to MLX format, fine-tuning with LoRA/QLoRA on Apple Silicon, or serving models via HTTP API.

6. Mai 2026
prompt-engineering
Softwareentwickler

Crafting effective prompts for LLMs. Use when designing prompts, improving output quality, structuring complex instructions, or debugging poor model responses.

6. Mai 2026
pytorch
Informatik- und Informationsforschungswissenschaftler

Building and training neural networks with PyTorch. Use when implementing deep learning models, training loops, data pipelines, model optimization with torch.compile, distributed training, or deploying PyTorch models.

6. Mai 2026
qlora
Softwareentwickler

Memory-efficient fine-tuning with 4-bit quantization and LoRA adapters. Use when fine-tuning large models (7B+) on consumer GPUs, when VRAM is limited, or when standard LoRA still exceeds memory. Builds on the lora skill.

6. Mai 2026
rlhf
Informatik- und Informationsforschungswissenschaftler

Understanding Reinforcement Learning from Human Feedback (RLHF) for aligning language models. Use when learning about preference data, reward modeling, policy optimization, or direct alignment algorithms like DPO.

6. Mai 2026
Es werden 8 von 9 gesammelten Skills angezeigt.
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