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

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, ...

Data School Kevin Markham’s data science and machine learning tutorials using Python and well-known tools like Scikit-Learn and Pandas are the main focus of Data School.

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 ...

Python has a plethora of machine learning libraries, but the top 5 libraries are TensorFlow, Keras, PyTorch, Scikit-learn, and Pandas. These libraries offer a wide range of tools for various ...

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

Anaconda Python Anaconda has come to prominence as a major Python distribution, not just for data science and machine learning but for general purpose Python development as well.

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 ...

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.