Training a Machine Learning Algorithm with Python Using the Iris Flowers Dataset For this example, we will be using the Jupyter Notebook to train a machine learning algorithm with the classic Iris ...

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

As a Python library for machine learning, with deliberately limited scope, Scikit-learn is very good. It has a wide assortment of well-established algorithms, with integrated graphics.

And, of course, Python is used extensively within Netflix's machine-learning algorithms for things like content recommendations, artwork personalization, and marketing.

From Python and Java to C++, R and Lisp, these languages offer powerful capabilities for working with machine learning algorithms to build AI apps.

Apart from automations, this article will assist those who want to learn more about data science and how Python can help. In the example below, I use an e-commerce data set to build a regression ...

Intel DAAL provides Python with a rich set of algorithms, ranging from the most basic descriptive statistics for datasets to more advanced data mining and machine learning algorithms.

Intel DAAL provides a rich set of algorithms, ranging from the most basic descriptive statistics for datasets to more advanced data mining and machine learning algorithms. Python can easily utilize ...

But it’s precisely that “programming background” that makes Python the clear winner for developers or others interested in big data, artificial intelligence (AI) and deep learning algorithms.

Machine learning is hard. Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of ...