Machine learning programming is an in-demand skill. Learn how to program an ML application with Python in this tutorial.

The book “ Introduction to Machine Learning with Python “ present detailed practice exercises for offering a comprehensive introduction to machine learning techniques along with basics of Python.

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, ...

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 ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

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.

Snowpark for Python gives data scientists a nice way to do DataFrame-style programming against the Snowflake data warehouse, including the ability to set up full-blown machine learning pipelines ...

PyTorch 1.10 is production ready, with a rich ecosystem of tools and libraries for deep learning, computer vision, natural language processing, and more. Here's how to get started with PyTorch.

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

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 ...