Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
AI & Analytics Engine
Akkio
Aureo.io
B2Metric ML Studio
No-Code AI Toolkit
Graphite Note
Ever Efficient AI
Baselight.app
The PI.EXCHANGE AI & Analytics Engine (the Engine) is a Data Science and Machine Learning (ML) platform that empowers everyone, even novice users, to affordably build high-performance ML applications in minutes or hours, not weeks or months.
The easy-to-use connected toolchain provides everything you will need to go from raw data to predictions and insights within a single pipeline. Manual and repetitive machine learning tasks are automated, and the Engine's intelligent features help guide the user end-to-end. So, whether you are building a small pilot project with no dedicated data science resources, or are deploying large-scale enterprise ML systems, you can equip your existing team with the right tool to build meaningful solutions, fast. The Engine gives users the flexibility to customize their ML pipeline from scratch for classification, regression, time-series, or clustering problems or to select an ML solution template to develop their ML application. While both ML development options are guided and require no-coding experience, the latter requires only articulation of business requirements and problem context via a few key steps - everything else is taken care of.
Notable AI solutions include: Customer Churn Prediction Leveraging your manufacturing data to build predictive maintenance strategies Predict online fraudulent transactions and reduce false positives and; Optimize logistics decision-making
Matplotlib AI & Analytics EngineBased on our record, Matplotlib seems to be a lot more popular than AI & Analytics Engine. While we know about 114 links to Matplotlib, we've tracked only 1 mention of AI & Analytics Engine. 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 / 7 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 8 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
DISCLAIMER: Hello everyone, my name is Fyona & I work in Marketing at PI.EXCHANGE. I wanted to share an EXCITING news regarding our upcoming release that I think can be helpful to many! The AI & Analytics Engine will be offering a Machine Learning (ML) Solution Templates, starting with our Customer Churn Prediction Template. Source: over 3 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Akkio - No-Code AI models right from your browser
NumPy - NumPy is the fundamental package for scientific computing with Python
Aureo.io - Aureo.io Makes AI Simple, Fast & Easy to Integrate
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
B2Metric ML Studio - Automated Machine Learning Platform
