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 ...

Figure 1. Popularity of machine learning languages (January 2019) In this article, you’ll learn why Python is especially successful for machine learning and other uses involving data science.

Teaching yourself Python machine learning can be a daunting task if you don’t know where to start. Fortunately, there are plenty of good introductory books and online courses that teach you the ...

Machine learning apps use Python’s memory-managed constructions more for the sake of organizing an application’s logic or data flow than for performing actual computation work.

New and seasoned data scientists can utilize ELI5 thanks to its simple user interface. 6. Eli5 ELI5 is a Python package that helps to debug machine learning classifiers and explain their predictions.

Python libraries: Python machine learning books usually use ScikitLearn (and sometimes SciPy) to implement algorithms. Books on deep learning cover TensorFlow, Keras, and PyTorch.

In this video, we implement the Adam optimization algorithm from scratch using pure Python. You'll learn how Adam combines ...

Too many false negatives, and you’ll soon be out of business. Machine learning makes it possible to analyze someone’s purchase history and determine whether a purchase is likely to be good or bad.

While Ronacher contributes little to Flask today – because new Python features for data science don't interest him – it's become popular for deploying machine-learning models thanks to an ...

The book “ Introduction to Machine Learning with Python “ has made explanation on Machine Learning with Python from basics to the advanced level so as to assist beginners in building strong ...