Artificial intelligence (AI) frameworks play an important part in machine learning. There are more than a dozen open-source AI frameworks available to data scientists and engineers in the market. Google TensorFlow is one of the more popular ones. It comes feature-packed with tools, libraries, pre-packaged models, and more.
Other popular frameworks include PyTorch and Caffe. One of the challenges is determining which one is the best fit for a particular use case. Use cases vary widely. Image classification, computer vision, anomaly detection are just a few of many. PyTorch, is a solid alternative for TensorFlow, depending on the use case. Scikit-learn works well in data analysis and data mining. Facebook, the founder of PyTorch continues to invest in it, as it plays an important part in the technology stack.
Here are ten popular open-source artificial intelligent frameworks.
| Framework | Language | Type | Use Cases |
|---|---|---|---|
| Accord.Net | C++ | Classification, regression, and clustering | Audio. Image processing. Computer vision. |
| Apache Mahout | Java / Scala | Distributed linear algebra framework | Ideal for mathematicians and statisticians. |
| Caffe | C++ | Deep Learning | Image classification. Speech. Multimedia. |
| Keras | Python | Deep Learning | High-level API. Tightly integrated with TensorFlow. |
| MLPack | C++ | “Swiss army knife” of methods and functions | Supports NeighborSearch. K-Means, and RangeSearch. |
| PyTorch | Python | Dynamic neural nets and Tensor computation | 2nd most popular framework. Developed by Facebook. |
| Scikit-learn | Python | Classification, regression, and clustering | Data mining. Data analysis. Developed SciPy, NumPy, and motplotlib. |
| Spark MLib | Java, Scala, Python, and R | Classification, regression, clustering, and more | 9x faster than Mahout. Used for matching learning pipelines. |
| Torch | Lua / LuaJIT | Deep Learning | Supports multi-dimensional arrays. GPUs ready. Computer vision. Image classification. Audio, and video. |
| Theano | Python | Used to evaluate mathematical expressions | Integrated with NumPy. Supports multi-dimensional arrays. Supports GPU’s. |