10 Python Libraries And Frameworks For Solving Difficult Machine Learning problems!
If you’re looking to get started in machine learning with Python, you’ll need to know which libraries and frameworks to use. Read on to find out more!
Python is a versatile language and is being used extensively in various fields such as web development, data science, artificial intelligence, and machine learning. In the world of machine learning, Python has proved to be a powerful platform with a vast array of libraries and frameworks.
In this article, we will discuss the top 10 Python libraries and frameworks for machine learning.
- TensorFlow
TensorFlow is an open-source library for data analysis and machine learning. Developed by Google, TensorFlow is one of the most popular and powerful libraries for deep learning. It provides a high-level API to define and operate on Tensors, which are data structures similar to arrays.
TensorFlow also provides lower-level APIs for constructing custom training algorithms. It has been used in a number of real-world applications, such as Google’s Street View for recognizing addresses and Google Photos for image search.
2. Scikit-learn
Scikit-learn is a Python library for data science and machine learning. It is used…
