Machine learning frameworks are software libraries that provide the tools and infrastructure needed to develop and deploy machine learning models. They make it easier to build machine learning applications by abstracting away the complexity of the underlying algorithms.
Here are the top 10 machine learning frameworks in 2023:
TensorFlow
PyTorch
Scikit-learn
Apache Spark
MicrosoftML
XGBoost
LightGBM
CatBoost
Amazon SageMaker
Google Cloud ML Engine
These frameworks are used for a wide range of machine learning tasks, including image classification, natural language processing, and speech recognition. They are a valuable tool for anyone who wants to build machine learning applications.
The best framework for you will depend on your specific needs and requirements. If you are a beginner, I recommend starting with Scikit-learn. It is a good choice for beginners because it is easy to learn and use. If you are looking for a more powerful framework, I recommend TensorFlow or PyTorch. These frameworks are more complex, but they offer more flexibility and expressiveness.
