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Top 11 Machine Learning Software You Must Know

https://pythongeeks.org/machine-learning-softwares/

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Top 11 Machine Learning Software You Must Know

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  1. TOP 11 MACHINE LEARNING SOFTWARE YOU MUST KNOW

  2. While we all agree that Machine Learning is the stepping stone for future technological development, we also have to make efforts to learn and develop this system. But, for doing this, we first need to understand the basics of how this technology is developed and what tools we need to use. While there are many sources to help you learn the basics, many would agree that going through these resources and understanding them can be quite tiresome. That’s why this article from PythonGeeks would help you to find out the most efficient Software Services that you can use as the building blocks for Machine Learning algorithms.

  3. Software Used for Machine Learning 1. TensorFlow One of the most efficient and famous tools in the field of Machine Learning, TensorFlow is an open-source platform for the implementation of Machine Learning Algorithms. Written in major programming languages like C++, Python, CUDA, you can use TensorFlow on all of the major Operating Systems like Windows, MacOS, and Linux Kernel. It provides a wide range of JavaScript libraries for dataflow programming.

  4. 2. PyTorch PyTorch is another great library to implement Machine Learning algorithms. As you could have guessed it from the name itself this tool is Torch-based. Torch, in simple words, could be a Lua-based computing framework used as a scripting language for Machine Learning libraries. 3. Shogun Like previously discussed tools, Shogun is another Software that helps you with Machine Learning Algorithms. Built-in C++, it facilitates you with various data structures and algorithms. Shogun provides libraries that are extensively made for research and educational purposes.

  5. 4. SciKit Learn Written in languages like Python, C and C++, SciKit Learn provides various Python libraries which could be effectively used for Machine Learning Development. It could be operated on all the major OS and is effectively used for its Python Libraries. This tool is predominantly used by researchers for implementing algorithms like Classification, Regression, Clustering, Model Selection while the list goes on. 5. Apache Mahout Being a cross-platform software, Apache Mahout is a really effective library if your area of concern is Mathematics, Statistics, and other Data Science queries. Built in Java and Scala, it provides an extensive range of libraries for execution of data science algorithms like Preprocessing, Regression, Clustering and others. Its implementations are an extension of Apache Hadoop Platform, which makes use of Map/Reduce paradigms.

  6. 6. Accord.Net Built in C# this Machine Learning tool is quite handy when it comes to handling problems related to Kernel methods, Hypothesis tests, Distribution and Clustering. It is extensively used for processing image and audio. It proves to be an effective framework for pattern recognition, statistical data processing and linear algebra. 7. KNIME Widely used in the field of data analysis, the Konstanz Information Miner, more commonly known as KNIME, is a reporting and integration platform. It follows a unique Modular pipelining, called “Building Blocks of Analysis” concept for machine learning and data mining. .

  7. 8. Apache Spark MLlib Spark is a much heard tool now-a-days. It is a powerful data streaming service. Apart from that, it also facilitates you with various machine learning algorithms with its MLlib. You can perform iterative computations and achieve better results with the help of Spark. With its libraries, you can easily integrate any of the Hadoop source along with machine learning algorithms for efficient work. 9. Amazon Machine Learning Being a cloud-based platform, AML is a robust machine learning software, which you can use as a web or mobile app developer. It is mainly used for prediction algorithms in addition to handling database queries. It can also integrate data from multiple sources like Amazon S3, RDS and many more. .

  8. 10. Weka Written in Java, you can use Weka when you’ve to work with data mining algorithms. Apart from the fact that you can operate it from all the leading operating systems like Windows, macOS, and Linux Kernel, Weka is a really powerful tool for mathematical modeling. 11. Rapid Miner If you are looking for a platform for using Machine Learning algorithms, deep learning, predictive analytics and more, then Rapid Miner is a great tool for you. You can also use it for research, educational as well as application development. .

  9. Conclusion Now that you are familiar with all the leading machine learning software, you’ll now be able to get your hands on learning these. According to your requirements, you’ll now be able to choose your favorable framework. With this curated list of tools, you can now provide your customers with an effective software development solution as per their choice.

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