With freely available open-source tools, developers can use Google or Facebook’s experience and incorporate artificial intelligence into their applications.
Developers who deal with the topic of artificial intelligence and machine learning can, for example, write apps for better speech recognition or take their self-developed applications to a new level. This article provides a list of popular open-source solutions.
Developers can use the experience of software giants like Google or Facebook to equip their apps with artificial intelligence. The frameworks work with the latest development environments and programming languages. In most cases, no new knowledge is required to make your apps more effective and intelligent.
Here are the best AI tools that you should explore:
Caffe2 deep learning framework
The deep learning framework Caffe was initially developed at the University of California. Facebook now employs the inventor. It is for the development of software responsible for AI. Facebook is actively driving the development of coffee. Graphics processors from NVidia are employed to ensure that the solution has optimum performance. The software is accessible as an open-source system.
Caffe can be used for speech recognition, the recognition and classification of images, or for the development of natural languages in AI devices. If you want to experiment with artificial intelligence, you are in good hands with Caffe2. The developers provide templates with which the user can be tested. Caffe has interfaces to C ++ and Python. Caffe2 can also be used for neural networks and generally also works with smartphones.
The software is also essential for Facebook, as the social network wants to focus more on augmented reality (AR) in the future. AR can combine the artificial world with the real world, creating new types of programs that can interact with the real world.
scikit-learn – machine learning with Python
The scikit-learn library which is derived from SciPy Toolkit, is based on the Python programming language. Packages like NumPy, SciPy, or Matplotlib are utilized by Scikit-learn to write mathematical, scientific, or statistical programs in Python. For that, too, data Mining and data analysis can be used with scikit-learn.
Scit-learn is available free of charge under the BSD license. This solution is also able to create applications for artificial intelligence. One example is recognizing bots or developing apps for voice assistants and other solutions for artificial intelligence. Scikit-learn can therefore distinguish messages created by computer programs on the Internet from human-created texts.
Thanks to the active community and the elaborated documentation, results can be achieved quickly. Scikit-Learn also works with other packages, such as Pandas or TensorFlow.
Machine learning with Shogun
The machine learning software ” Shogun ” is also a known solution in the field of artificial intelligence. The library supports numerous languages, such as Python, Octave, R, Java / Scala, Lua, C #, and Ruby. This enables scientific programs to be created based on Linux / Unix, macOS, and Windows.
Therefore, the solution is not dependent on trends in programming languages and can be used flexibly with the language that is best suited for the respective object. A change is possible at any time, so that developers do not maneuver into a dead end if the programming language currently used is less common in the future.
Accord.NET Framework is software for creating machine learning software. It also offers libraries for audio and image processing. The solution is the successor to AForge.NET. The Framework is a .NET framework combined with audio and image processing libraries written entirely in C #.
The Framework is used to create production-compatible signal processing and statistical applications for commercial use. A collection of sample applications enables a quick start and is quickly ready for use. Documentation and a wiki help you to familiarize yourself with it.
Apache Mahout – Big Data meets Machine Learning
Apache Mahout is a library of scalable machine learning algorithms based on Apache Hadoop and MapReduce. The advantage of the solution is that it also works in big data environments. Apache Mahout enables machine learning with big data environments, and can work directly with Apache Hadoop. Statistical calculations can also be carried out.
Mahout is, therefore, an essential open-source software when it comes to developing software in the field of artificial intelligence. The solution works with other big data products, such as Apache Spark. The interactive shell enables a direct connection to various apps. For this purpose, a Scala-based library is used that works similarly to R.
Mahout uses this as a Domain Specific Language (DSL), which can be compared to R. If you know R, you will quickly get along with Mahout. Spark and Flink can be used in parallel. The code that was written with DSL for Spark usually also works with Flink.
Artificial Intelligence and Machine Learning have slowly started taking their place into the day-to-day development methodologies. Be it a web application development company, an Android or Swift app development company, or a Progressive Web App development company, these emerging technologies have helped achieve feats once never thought were possible.