amazon-sagemaker-managed-spot-training

? Serverless Framework – Effortlessly build apps that auto-scale, incur zero costs when idle, and require minimal maintenance using AWS Lambda and other managed cloud services.

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Enhanced ChatGPT Clone: Features Agents, DeepSeek, Anthropic, AWS, OpenAI, Assistants API, Azure, Groq, o1, GPT-4o, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active project.

Pulumi - Infrastructure as Code in any programming language ?

A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources. Featuring the Fiery Meter of AWSome.

Python Serverless Microframework for AWS

Example ? Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using ? Amazon SageMaker.

A declarative JavaScript library for application development using cloud services.

The AWS Serverless Application Model (AWS SAM) transform is a AWS CloudFormation macro that transforms SAM templates into CloudFormation templates.

Deploy infinitely scalable serverless apps, apis, and sites in seconds to AWS.