MLflow
MongoDB
MLflow | MongoDB | |
---|---|---|
56 | 249 | |
17,284 | 25,453 | |
1.3% | 0.6% | |
9.9 | 10.0 | |
5 days ago | 6 days ago | |
Python | C++ | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
MLflow
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Observations on MLOps–A Fragmented Mosaic of Mismatched Expectations
How can this be? The current state of practice in AI/ML work requires adaptivity, which is uncommon in classical computational fields. There are myriad tools that capture the work across the many instances of the AI/ML lifecycle. The idea that any one tool could sufficiently capture the dynamic work is unrealistic. Take, for example, an experiment tracking tool like W&B or MLFlow; some form of experiment tracking is necessary in typical model training lifecycles. Such a tool requires some notion of a dataset. However, a tool focusing on experiment tracking is orthogonal to the needs of analyzing model performance at the data sample level, which is critical to understanding the failure modes of models. The way one does this depends on the type of data and the AI/ML task at hand. In other words, MLOps is inherently an intricate mosaic, as the capabilities and best practices of AI/ML work evolve.
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My Favorite DevTools to Build AI/ML Applications!
MLflow is an open-source platform for managing the end-to-end machine learning lifecycle. It includes features for experiment tracking, model versioning, and deployment, enabling developers to track and compare experiments, package models into reproducible runs, and manage model deployment across multiple environments.
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.
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cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
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EL5: Difference between OpenLLM, LangChain, MLFlow
MLFlow - http://mlflow.org
- Explain me how websites like Dall-E, chatgpt, thispersondoesntexit process the user data so quickly
- [D] What licensed software do you use for machine learning experimentation tracking?
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Exploring MLOps Tools and Frameworks: Enhancing Machine Learning Operations
MLflow:
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Options for configuration of python libraries - Stack Overflow
In search for a tool that needs comparable configuration I looked into mlflow and found this. https://github.com/mlflow/mlflow/blob/master/mlflow/environment_variables.py There they define a class _EnvironmentVariable and create many objects out of it, for any variable they need. The get method of this class is in principle a decorated os.getenv. Maybe that is something I can take as orientation.
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[D] Is there a tool to keep track of my ML experiments?
I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
MongoDB
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System Design: Databases and DBMS
MongoDB
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From Zero to CRUD Hero: Building Your First Backend API in JavaScript
First, visit MongoDB Atlas and create an account, or sign in if you already have one. This article will guide you through the process of creating a MongoDB account. You should be redirected to your dashboard once you have completed the process. Locate the Connect button and click it.
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Understanding SQL vs. NoSQL Databases: A Beginner's Guide
On the other hand, NoSQL databases are non-relational databases. They store data in flexible, JSON-like documents, key-value pairs, or wide-column stores. Examples include MongoDB, Couchbase, and Cassandra.
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Building Llama as a Service (LaaS)
I built each API with Node.js, Express, and Docker. Services connected to a NoSQL MongoDB database.
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Time Series Blob Data: ReductStore vs. MongoDB
In edge computing, managing time series blob data efficiently is critical for performance-sensitive applications. This blog post will compare ReductStore, a specialized time series database for unstructured data, and MongoDB, a widely-used NoSQL database.
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Build Your Own Uptime Monitor with MeteorJS + Fetch + Plotly.js ☄️🔭
MongoDB to store our data as documents, close to JS objects
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How to choose the right type of database
MongoDB: Known for its ease of development and strong community support, MongoDB is effective in scenarios where flexible schema and rapid iteration are more critical than strict ACID compliance.
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How to create a dynamic AI Discord bot with TypeScript
MongoDB
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Mastering Microservices: A Hands-On Tutorial with Node.js, RabbitMQ, Nginx, and Docker
Ensure you have MongoDB installed for data storage. You can download MongoDB Community Server from MongoDB's official website or use the cloud cluster.
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How to Build & Deploy Scalable Microservices with NodeJS, TypeScript and Docker || A Comprehesive Guide
We will be using MongoDB as a database on both the Auth microservice and notifications microservice, sign up for a MongoDB Atlas account here incase you donot have one and donot have its desktop application(mongodb campass) installed and would like to use mongodb atlas. This cloud-based database service offers a free tier and simplifies the process of managing MongoDB databases.
What are some alternatives?
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
mongo-express - Web-based MongoDB admin interface, written with Node.js and express
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Marten - .NET Transactional Document DB and Event Store on PostgreSQL
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
LiteDB - LiteDB - A .NET NoSQL Document Store in a single data file
guildai - Experiment tracking, ML developer tools
LevelDB - LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
dvc - 🦉 ML Experiments and Data Management with Git
SQLAlchemy - The Database Toolkit for Python
tensorflow - An Open Source Machine Learning Framework for Everyone
Apache Ignite - Apache Ignite