Machine learning is a rapidly growing field, and there are numerous tools available to help developers and researchers build and deploy machine learning models. Here are some popular machine learning tools:
TensorFlow: An open-source library developed by Google Brain, TensorFlow is one of the most popular machine learning frameworks. It is widely used for deep learning applications.
PyTorch: Developed by Facebook's AI Research lab, PyTorch is another popular machine learning framework. It is known for its ease of use and dynamic computation graph.
Scikit-learn: A Python-based library for machine learning, Scikit-learn is widely used for data mining and data analysis. It provides simple and efficient tools for data analysis and modeling.
Keras: Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It is designed to enable fast experimentation with deep learning models.
Jupyter Notebook: Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It is widely used for data analysis and machine learning.