Top 17 Most Popular AI - Machine Learning Software Tools in 2020  

Machine learning comes with an extensive collection of Machine learning  tools & Software's.Machine Learning the algorithm is absolutely revolutionary.  This post will enable you to learn about best machine learning software's. We have incorporated the most popular machine learning Software's in this topic.

1. Shogun:

Shogun is One of the most popular open-source Machine Learning software. The various algorithm supported by Shogun are Support Vector Machine, Dimensionality reduction, Linear Discriminant Analysis & Clustering Algorithms.

2. Oryx 2:

It is renowned for end to end model development pertaining to collaborative filtering, classification, regression & also for clustering operations.

Oryx 2 takes the help of Lambda Architecture for real-time & large scale Machine Learning software processing.

Oryx 2 has got 3 tiers 

• The first tier is basically generic lambda tier that gives speed of a serving layer however, they are not related to Machine learning procedure.
• The second tier revolves around the need to provide Machine learning abstractions for selecting the hyper parameters.
• The role of third tier is to provide a platform for an end to end implementation.

3. H20.ai:

H2O's  deep learning platform  provides a scalable multi-layer Artificial Neutral Network(ANN). The best part about this ANN is that, it is made up of several components as well as parameters that can be altered depending on the types of data obtained. It also offers a rate annealing & adaptive learning rate to yield highly productive output.

Although the native H2O-3 is known for supporting only the standard feed-forward neutral network however, another version of H2O does support the Convolutional Neutral Networks as well as a Recurrent Neutral Networks.

4. Tensorflow:

It is considered as the standard name for Machine Learning software, when it comes to data science industry. It assist to build not only statistical Machine Learning software solution, but also deep learning by means of its extensive interface of CUDA GPUs.

In Tensorflow, a tensor is a multidimensional array which is the most basic data type of  TensorFlow.

For beginners of  Machine Learning software, TensorFlow is a must. It extends support & functions for various applications of Machine Learning .

5. Pytorch:

It has been developed by Facebook. It basically offers an advanced deep learning framework. It's key features are Deep Neutral Network & Tensors.

Pytorch plays an important role in developing rapid prototyping for research.

Uber's Probabilistic Programming Language is a classic example of Pytorch. It assists to design dynamic graph which in turn accelerates Machine Learning process.

6. Apache  Mahout:

It is basically an Open Source Machine Learning software which concentrates on two aspects:

• Collaborative Filtering.
• Classification.

These implementations are associated with Apache Hadoop Platform.

It's major features are stated below:

• Provides expressive Scale DSL & Distributed Linear Framework for the purpose of deep learning of computations.
• Extends native solvers for CPUs, GPUs & CUDA accelerators.

7. Weka:

It stands for Waikato Environment for Knowledge Analysis.

It consists of several Machine Learning software algorithms which are ready for use.These algorithms comes handy for data mining.

With minimal programming lines, such an open-source GUI interface can be used for the implementation of a Machine Learning software algorithm.

For a new entrant / fresher this software is highly recommended.

8. Keras:

Its greatest advantage revolves around the fact that, it is capable of running seamlessly on CPU & GPU.

It is basically an open-source neutral network library that extends support for python. It is known for its speed, ease while using & also for its modularity. One can use it for not only it's fast experimentation, but also for rapid prototyping.

One of the significant element of Keras is that it extend assistance  for the implementation of Convolutional as well as Recurrent Neural Networks & both.

 It is user friendly and enables users to readily implement neutral networks without thinking too much about the technical jargons.

9. Apache Spark MLLib:

It is a powerful data streaming platform having the following merits:

1. It extends a lot of Advanced Machine Learning features via MLlib.
2. It facilities a scalable Machine Learning platform by utilizing its APIs that enables the user to implement Machine Learning on real-time data.

Some of the algorithm supported by MLlib are classification, Logistic Decision Trees, Topic Modelling & Naive Bayes etc.

10. KNIME:

It's full form is Konstanz Information Miner. It is basically an integration platform as well as data analytics. KNIME helps to carry out various components of Machine Learning & data mining. It keeps on adding new development features.

One of the greatest advantages of  KNIME is that it supports the user to comprehend the data &  also in creating data science workflows, by utilizing components that are reusable in nature & easily available to all.

It blends several data sources for the purpose of carrying out data modelling, analysis & visualization eliminating the need for extensive programming.

11. Rapid Miner:

For the purpose of doing several activities like machine learning predictive analysis, text mining & data preparation etc , Rapid Miner provides an excellent integrated & comprehensive environment.

It has gained popularity for being able to reduce cost, avoid risk to a great degree & also for lightning-fast speed to generate revenue.

One of the key ingredient of RapidMiner is it's GUI based drag & drop feature that supports the user to design & develop data processing work flows which can be picked from 2000 nodes.

Recent Best & Popular Machine Learning software Tools (2020) :

12. Google Cloud ML Engine.

13. Amazon Machine Learning (AML).

14. Accord.NET.

15. Apache Singa.

16. Google ML Kit for Mobile.

17. Apple’s Core ML.

Conclusion:

Machine learning software's are getting upgraded. Machine learning is an evolving concept. It offers endless possibilities. These Machine learning software's are helpful & beneficial provided we have inside out information about them. The more we learn the better it is for us.