The Apache Spark large-scale data processing engine has a machine learning library called MLlib. It promises easy deployment on Hadoop with 100 times faster performance than MapReduce.
This company is dedicated to creating open source technology that uses AI to control the Internet of Things (IoT). They have released several open source natural language processing tools, and they have a crowdfunded IoT control device that looks like a very friendly robot.
Neuroph is an open source Java-based framework for developing neural network architectures. It's designed to be used by developers who are new to AI, offering quite a bit of online documentation.
Numenta is a company developing products based on a theory called Hierarchical Temporal Memory, which offers a framework for both biological and machine intelligence. NuPic is its open source platform based on this theory which can be used for data analysis, prediction and anomaly detection.
36. Open Cog
Another open source initiative, Open Cog is dedicated to "creating beneficial artificial general intelligence (AGI), with broad capabilities at the human level and ultimately beyond." The technology is currently in use at Hong Kong Polytechnic University, and the team is confident that they will soon have software capable of human preschool-level intelligence.
37. Oryx 2
Based on the architecture of Apache Spark and Apache Kafka, Oryx 2 is an application development framework specifically designed for real-time, large-scale machine learning. It's an open source project created by Cloudera.
Short for "Open Neural Networks," OpenNN is a predictive analytics library written in C++ that boasts high performance. It was developed by Artelnics, a software developer that specializes in creating data analysis software for enterprises.
This open source project offers machine learning tools for Python, with a focus on data mining and analysis. It builds on the work of several other open source projects, including NumPy, SciPy, and matplotlib.
Shogun describes itself as "a large-scale, machine-learning toolbox." It supports a wide variety of programming languages and offers classification, regression, dimensionality reduction, clustering, metric, multi-task, structured output, online learning feature hashing, ensemble methods and optimization capabilities.
According to its website, Theano has been "powering large-scale computationally intensive scientific investigations since 2007." It's a Python library for working with mathematical expressions involving multi-dimensional arrays efficiently, and it is useful for some deep learning applications.
Built to run on GPUs and based on LuaJIT, Torch is an open source scientific computing framework that supports a lot of machine learning algorithms. Community members have created Torch packages for machine learning, computer vision, signal processing, parallel processing and other AI applications.
Created by the team of developers behind Siri, Viv is a new AI platform controlled by conversational input. It learns constantly from the world around it, allowing it to expand its capabilities on a daily basis. The software isn't yet available for download, but the company behind it is currently seeking partners who are interested in integrating Viv into their own products.
Created by the machine learning group at the University of Waikato in New Zealand, WEKA enables data mining in Java applications. It includes machine learning algorithms for data pre-processing, classification, regression, clustering, association rules and visualization.
This commercial project is a knowledge engine that can answer questions on a huge variety of subjects, including math, languages, chemistry, dates, health, science, money, history and much more. Anyone can use the free version on the website above, or you can subscribe to the Pro service for around five or six dollars a month.