Dataiku VS ML.NET
Compare Dataiku VS ML.NET and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
featured
Dataiku
Scikit-learn
Pandas
NumPy
OpenCV
Exploratory
htm.java
WEKA
ML.NET
R Caret
H2O.ai
R MLstudio
Scikit-learn
TensorFlow
datarobot
Odury
Dataiku ML.NETBased on our record, ML.NET seems to be more popular. It has been mentiond 2 times since March 2021. 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.
Documentation - You can find tutorials and how-to guides in our documentation site. Probably the easiest way to get started is with the Model Builder extension in Visual Studio. Here's install instructions and a tutorial to help you start out. Source: almost 2 years ago
I would start right here- ML.Net Documentation. Source: almost 3 years ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
R Caret - Documentation for the caret package.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
H2O.ai - Democratizing Generative AI. Own your models: generative and predictive. We bring both super powers together with h2oGPT.
NumPy - NumPy is the fundamental package for scientific computing with Python
R MLstudio - The ML Studio is interactive for EDA, statistical modeling and machine learning applications.