Best Python libraries for Machine Learning - GeeksforGeeks
Oct 8, 2024 · Learn about the most popular and useful Python libraries for Machine Learning, such as NumPy, SciPy, Scikit-learn, Theano, TensorFlow, Keras, PyTorch, and Pandas. See examples of how to use them for various tasks, such as linear algebra, image manipulation, decision trees, and neural networks.
scikit-learn: machine learning in Python — scikit-learn 1.5.2 …
Machine Learning in Python. Getting Started Release Highlights for 1.5. Simple and efficient tools for predictive data analysis. Accessible to everybody, and reusable in various contexts. Built on NumPy, SciPy, and matplotlib. Open source, commercially usable - BSD license. Classification. Identifying which category an object belongs to.
Machine Learning Crash Course - Google Developers
Learn the fundamentals and advanced topics of machine learning with Google's fast-paced, practical introduction. Explore 12 modules with video lectures, interactive visualizations, and...
9 Best Python Libraries for Machine Learning - Coursera
Apr 4, 2024 · Learn about the most popular and useful Python libraries for machine learning projects, such as NumPy, Scikit-learn, TensorFlow, and more. Find out how to use them for data analysis, visualization, and model development.
15 Best Python Libraries for Machine and Deep Learning
Mar 7, 2022 · Learn about the most popular and useful Python libraries for ML and DL projects, such as NumPy, SciPy, scikit-learn, Theano, TensorFlow, Keras, and PyTorch. Compare their features, benefits, and drawbacks, and see how they can help you create and train neural networks and models.
Introduction to machine learning - Training | Microsoft Learn
Learn the basics of machine learning with Python, using Azure Machine Learning. Explore data, create and test a model, and load and use it with new data.
15 Best Machine Learning Libraries You Should Know in 2024
Aug 8, 2023 · Learn about 15 of the best machine learning libraries for various purposes, such as linear algebra, neural networks, data visualization, and more. Compare features, highlights, and bindings of each library in this comprehensive guide.
Machine Learning Introduction for Everyone - Coursera
Learn the fundamentals of machine learning and data science with this three-module course. Explore the history, applications, models, and evaluation of machine learning, and complete a final project to demonstrate your skills.
scikit-learn · PyPI
Sep 21, 2011 · scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and …
Machine Learning with Python Course (IBM) | Coursera
Dec 31, 2016 · Learn the fundamentals of Machine Learning with Python and apply them to real-world problems. This course covers regression, classification, clustering, and evaluation metrics with hands-on labs and projects.
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