MLflow
PostgreSQL
Our great sponsors
MLflow | PostgreSQL | |
---|---|---|
54 | 403 | |
17,021 | 14,445 | |
3.9% | 3.1% | |
9.9 | 9.9 | |
6 days ago | 4 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
-
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.
-
cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
-
EL5: Difference between OpenLLM, LangChain, MLFlow
MLFlow - http://mlflow.org
-
Exploring MLOps Tools and Frameworks: Enhancing Machine Learning Operations
MLflow:
-
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.
-
[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.
-
Looking for recommendations to monitor / detect data drifts over time
Dumb question, how does this lib compare to other libs like MLFlow, https://mlflow.org/?
-
Integrating Hugging Face Transformers & DagsHub
While Transformers already includes integration with MLflow, users still have to provide their own MLflow server, either locally or on a Cloud provider. And that can be a bit of a pain.
-
Any MLOps platform you use?
I have an old labmate who uses a similar setup with MLFlow and can endorse it.
MLflow - an open-source platform for managing your ML lifecycle. What’s great is that they also support popular Python libraries like TensorFlow, PyTorch, scikit-learn, and R.
PostgreSQL
-
From zero to hero: using SQL databases in Node.js made easy
Node.js, MySQL and PostgreSQL servers installed on your machine
-
I Deployed My Own Cute Lil’ Private Internet (a.k.a. VPC)
Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).
-
How to dump and restore a Postgres DB with new table ownership
I've used MySQL for years. But recently, I found myself working PostgreSQL and simple things like dumping and restoring a database are different enough that I decided to document the process. It's straightforward enough once I knew how.
-
Test Driving a Rails API - Part One
A running Rails application needs a database to connect to. You may already have your database of choice installed, but if not, I recommend PostgreSQL, or Postgres for short. On a Mac, probably the easiest way to install it is with Posrgres.app. Another option, the one I prefer, is to use Homebrew. With Homebrew installed, this command will install PostgreSQL version 16 along with libpq:
-
Um júnior e um teste técnico: The battle.
PostgreSQL
-
How to choose the right type of database
PostgreSQL: Offers a robust feature set and strong compliance with SQL standards, making it suitable for a wide range of applications, from simple to complex, particularly where data integrity and extensibility are key.
-
NoSQL Postgres: Add MongoDB compatibility to your Supabase projects with FerretDB
FerretDB is an open source document database that adds MongoDB compatibility to other database backends, such as Postgres and SQLite. By using FerretDB, developers can access familiar MongoDB features and tools using the same syntax and commands for many of their use cases.
-
Preventing SQL injection attacks in Node.js
To better understand how SQL injection works, let's quickly create a vulnerable app using Node.js, Express, and a PostgreSQL database. The application takes user input from a form, constructs a SQL query, and executes it against the database to fetch some data.
-
Full Stack Chat App with Socket.io
We'll use PostgreSQL, and first of all, you need to install PostgreSQL if you haven't installed it yet. https://www.postgresql.org/
-
Rust GraphQL APIs for NodeJS Developers: Introduction
In my usual NodeJS tech stack, which includes GraphQL, NestJS, SQL (predominantly PostgreSQL with MikroORM), I encountered these limitations. To overcome them, I've developed a new stack utilizing Rust, which still offers some ease of development:
What are some alternatives?
clearml - ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
guildai - Experiment tracking, ML developer tools
dvc - 🦉 ML Experiments and Data Management with Git
psycopg2 - PostgreSQL database adapter for the Python programming language
tensorflow - An Open Source Machine Learning Framework for Everyone
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
H2O - 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.
neptune-client - :ledger: The MLOps stack component for experiment tracking
dagster - An orchestration platform for the development, production, and observation of data assets.
gensim - Topic Modelling for Humans