These are the top Python AI projects used by AI experts around the world.
Artificial intelligence is one of the most advanced topics in the technology industry. The implementation of AI applications is rapidly increasing, and technology enthusiasts need to keep pace with this evolving area in order to work with AI-powered tools and applications. The languages implemented in AI and ML projects is Python. This article provides a list of open source AI projects and applications using Python.
TensorFlow
Listed as one of the leading open source projects for artificial intelligence with Python. TensorFlow is a Google product that helps developers build and train machine learning models. It has helped machine learning engineers turn prototypes into work materials quickly and efficiently. It currently has thousands of users all over the world and is a go to solution for AI.
Chainer
Chainer is a Python-based framework for working on neural networks. It is compatible with multiple network architectures. concurrently, including recurring networks, recursive networks, and feedforward networks. In addition, it enables the CUDA calculation so that users can use GPUs with very few lines of code.
PyTorch
PyTorch helps with prototype research so users can implement products faster. It enables streaming between graphic modes via TorchScript and provides distributed training that users can scale. This model is available on multiple cloud platforms and has numerous tools in its ecosystem to support NLP, Computer Vision, and other solutions.
Shogun
Shogun is a machine learning library and helps create efficient machine learning models. Shogun is not based entirely on Python as it can be used with various other programming languages such as C #, Lua, Ruby, and R to name a few. allows you to combine different classes of algorithms and data presentations so that users can quickly prototype data pipelines.
Gensim
This is an open source Python library that can parse plain text files for a deeper understanding of semantic structures, and also retrieve semantically similar files and perform other tasks. Like any other Python library, it is scalable and platform dependent.
Statsmodels
It is a Python module that provides classes and functions for estimating various statistical models, running tests, and exploring statistical data. Supports specification of models using formulas and Rstyle data frames.
Theano
Theano enables users to efficiently evaluate math operations, including multidimensional matrices. It is used in building deep learning projects. The high speeds of Nano give C implementations a tough competition for problems with large amounts of data. It is programmed to take structures and convert them into efficient codes.
Keras
Keras is an accessible API for neural networks. It is based on Python and can also be run on CNTK, TensorFlow and Theano. It was written in Python and follows best practices for reducing cognitive pressure. Makes working on deep learning projects more efficient.
NuPIC
It is an open source project based on the HTM theory (Hierarchical Temporal Memory). His deep experience in theoretical neuroscientific research has led to tremendous discoveries about how the brain works. Its deep learning systems have shown impressive performances.
Scikitlearn
It is a Python-based application and tool library that can be used for data mining and data analysis. This tool has great accessibility and is extremely easy to use. The developers have integrated it with NumPy and SciPy to make it easier for beginners and advanced users alike.
