Top 5 Machine Learning software

In the last decade or so Artificial Technology has commendably taken a leap forward. So much so that it has become our daily driver. But how did Artificial Intelligence become a thing? It all happened because of Machine Learning. A system that adapts, learns and rectified automatically. Let’s list the top 5 software that complements machine learning and puts it in the spotlight.

 

Tensor Flow

About

Developed by Google Brain team on 9th November 2015, Tensor Flow runs on multiple CPUs, GPUs and GPUs. It is an open source software for programming data flows of varied types.

 

Features

Tensor Flow promises balanced C APIs and Python with any backward on API. It also has released Java, C++, Swift and Go.

 

Availability

Tensor Flow is compatible with Linux, Windows, macOS, IOS, and Android.

 

Scikit Learn

 

About

Focused on writing Python and sometimes the initial algorithms in Cython, Scikit Learn is a free machine learning software. It was initially developed by David Cournapeau at Google Summer of Code.

 

Features

Support vector machines, random decision forests, classification, regression to k-mean and DBSCAN the Scikit Learn provides an array of features. Additionally, it interoperates Numpy and SciPy, Pythons numeric and scientific library.

 

Availability

Scikit Learn is compatible with Linux, Windows, macOS and updated IOS version

 

XGBoost

 

About

One of the most flourishing machine learning software for tabulated and structured data. XGBoost has initially developed Tianqi Chen and owned by DMLC or Distributed Machine Learning Community. It is an application of gradient boosted decision trees.

 

Features

Interfaces supported by XGBoost are CLI, C++, Python, R, Julia, and Java. The software is concentrating on delivering speed and modular performance. Including Modular, Systems and Algorithm feature.

 

For a more conclusive Introduction to Machine Learning just follow the link or you can always refer to my other articles where I cover it in depth.

 

Availability

XGBoost is compatible with Linux, Windows, Ubuntu, macOS, and updated IOS versions.

 

Torch

 

About

An open source machine learning software primarily focused on GPUs. Originally developed by Ronan Collobert, Koray Kavukcuoglu, and Clement Farabet. Know for its easy to understand and fast scripting language through LuaLIT and C/ CUDA.

 

Features

Comes with a number of features. Listed- linear algebra routines, neural network, and energy-based models, a powerful N-dimensional array and more.

 

Availability

The Torch is compatible with Linux, Windows, macOS and updated IOS and Android versions.

 

H2O

 

About

Again, an open source machine learning framework, H20 was developed and is owned by a company named H20.ai. Famously known for its usage in cloud-based systems and Apache Hadoop. Written in 3 languages mainly R, Python, and Java, with H2O its all about capacity model works.

 

Features

Among various other features, H2O can withstand large model analysis. Also, dictates smooth cloud-based computing and uses Iterative methods for faster real time results.

 

Availability

H2O is compatible with Linux, Windows, and macOS.

 

Conclusion

These were my top 5 picks of software one can use for machine learning. Ultimately it depends on an individual’s need if it’s speed or prolonged data analysis. The software you use will depend on variables such factors. Each has its own specific benefits. Step into the artificial reality and discover new technological advancements with this software.

 

 

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