Python has become the most popular data science and machine learning programming language. But in order to obtain effective data and results, it’s important that you have a basic understanding of how ...

Learn how to create a simple neural network, and a more accurate convolutional neural network, with the PyTorch deep learning library PyTorch is a Python-based tensor computing library with high-level ...

Python is used to power platforms, perform data analysis, and run their machine learning models. Get started with Python for technical SEO.

Machine Learning: Theory & Hands-On Practice with Python Specialization In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use ...

This book is edited by Li Hui and Chen Yanyan, with associate editors Yang Yu, Gao Yong, Zhang Qiaosheng, Bi Ye, and Liu Dengzhi. It is rich in content, covering 32 theories and 32 practical cases, ...

To improve accessibility, they used Google Colab, a free, cloud-based platform to write and run Python codes—which means users don't have to install software to follow the tutorial.

In this article, we first provide an overview of machine learning and clarify its difference from statistical inference. Then, we review Scikit-learn, a machine learning package in the Python ...

Discover five powerful Python libraries that enable data scientists to interpret and explain machine learning models effectively.

Find out what makes Python a versatile powerhouse for modern software development—from data science to machine learning, systems automation, web and API development, and more.

Not necessarily for the data-science and machine-learning communities built around Python extensions like NumPy and SciPy, but as a general programming language.