Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Algorithmia
MCenter
5Analytics
Spell
neptune.ai
MuleSoft Anypoint Platform
Zapier
Datadog
Matplotlib AlgorithmiaAlgorithmia is recommended for data scientists, machine learning engineers, and developers who need a flexible and scalable environment to deploy, manage, and share AI and machine learning models. It is particularly suitable for teams seeking to collaborate and leverage pre-built algorithms from a community-driven marketplace. Businesses looking to integrate machine learning capabilities into their operations without extensive infrastructure management will also benefit from Algorithmia's offerings.
Based on our record, Matplotlib seems to be a lot more popular than Algorithmia. While we know about 114 links to Matplotlib, we've tracked only 5 mentions of Algorithmia. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
To push a model into production, there are additional concerns which the tools in the versioning, deployment and release space aim to solve. This includes obtaining adequate infrastructure to run the model reliably and facilitating easy model release or rollback. Solutions in the MLOps space includes Kubeflow, Pachyderm and Algorithmia. - Source: dev.to / over 4 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 4 years ago
Algorithmia advertises themselves as an MLops platform for data scientists, and they provide an easy way to host models on a scalable REST API. Source: over 4 years ago
Seems similar to https://algorithmia.com. Source: over 4 years ago
Algorithmia.com โ Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / almost 5 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
MCenter - Machine Learning Operationalization
NumPy - NumPy is the fundamental package for scientific computing with Python
5Analytics - The 5Analytics AI platform enables you to use artificial intelligence to automate important commercial decisions and implement digital business models.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
Spell - Deep Learning and AI accessible to everyone
