The top 10 open-source software in AI and ML to explore are:
1. TensorFlow: Developed by Google, TensorFlow is a widely-used AI library for numerical computation and machine learning.
2. PyTorch: PyTorch is a popular open-source deep learning framework widely used for computer vision and natural language processing tasks.
3. Scikit-learn: Scikit-learn is a simple and efficient machine learning library in Python, providing various algorithms and tools for data analysis and modeling.
4. Keras: Keras is a user-friendly deep learning library that can run on top of TensorFlow, Theano, or Microsoft Cognitive Toolkit (CNTK).
5. Apache MXNet: Apache MXNet is a highly scalable and efficient deep learning framework used for neural networks and deep learning models.
6. Caffe: Caffe is a fast and lightweight deep learning framework favored for its speed, expressive architecture, and easy deployment options.
7. Theano: Theano is a Python library used for efficient mathematical calculations, particularly for defining, optimizing, and evaluating mathematical functions.
8. OpenCV: OpenCV (Open Source Computer Vision) is a powerful library for computer vision tasks, such as image and video processing.
9. H2O.ai: H2O.ai is an open-source AI platform with an interactive user interface that provides a distributed environment for building and deploying ML models.
10. Apache Spark: Although primarily a big data processing framework, Apache Spark also offers MLlib, a scalable machine learning library with various algorithms and tools.
These open-source software packages provide a wide range of functionalities and are extensively used by researchers, developers, and data scientists in the field of AI and ML.