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Full reference of LinkedIn answers 2024 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers
Best Practices on Recommendation Systems
☁️ Build multimodal AI applications with cloud-native stack
⚡️HivisionIDPhotos: a lightweight and efficient AI ID photos tools. 一个轻量级的AI证件照制作算法。
Machine Learning Engineering Open Book
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
Workflow Engine for Kubernetes
A curated list for awesome kubernetes sources :ship::tada:
The Cloud Native AI Platform
Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang
A hyperparameter optimization framework
Learn ML engineering for free in 4 months! Register here 👇🏼
A curated list of references for MLOps
A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources. Featuring the Fiery Meter of AWSome.
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Open Machine Learning Course
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
Build, Manage and Deploy AI/ML Systems
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Instant Kubernetes-Native Application Observability
Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models