Top Machine Learning Software

Machine Learning is the astonishing technology if you use it in a correct way. How fascinating it can be to build a machine that behaves like a human being to a great extent. So, mastering machine learning tools will let you play with data, train your models, discover new methods, and create your own algorithms. The machine learning comes with an extensive collection of ML tools, platforms, and software. Moreover, machine learning tools are continuously evolving everyday with new technologies. Below is the top machine learning software.


NET Machine Learning: F# and Accord.NET is an extension of the .net machine learning framework that is combined with the audio and image processing libraries which are written in C language. It includes a couple of libraries for an extensive range of programs, for statistical processing, pattern recognition, and linear algebra. It is used for developing production-grade computer vision, computer audition and signal processing, and statistics applications.

Google Cloud ML Engine

In case if you choose training your classifier sets on thousands of data, then a laptop or PC might work well.  On the other way around, if you have millions of data and algorithms take the maximum amount of time for executing. So, Google Cloud ML engine comes into the picture which is a hosted wherein developers and data scientists can develop and run the top-notch learning models.

Jupyter Notebook

NET Interactive: Jupyter Notebooks with .NET Core - Preview 2

Jupyter notebook is one of the most widely used machine learning tools among all.  It is very fast processing as well as an efficient platform and supports three languages such as viz. Julia, R, Python. The name of Jupyter is formed by the combination of these three programming languages. So, Jupyter Notebook will allow the user to store and share the live code in the form of notebooks. Also, users can access through a GUI. Jupyter Notebook is ideal for machine learning tools.

Apache Mahout

Apache Mahout is a linear algebra framework and mathematically expressive Scala DSL. This can be a free and open-source project of the Apache Software Foundation. So, the intention of this framework is to put in force an algorithm quick for record scientists, mathematicians, and statisticians.

The above-mentioned software is the most popular and widely used in machine learning tools and all these will use different programming languages and run on them. Hope that I have covered all the topics in my article about top machine learning software. Thanks for reading!

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