Python

Employing Python to make machine learning predictions can be a daunting task, especially if your goal is to create a real-time solution. However, Tensorflow and Scikit-Learn can significantly speed up implementation. In this article, Toptal Python Developer Guillaume Ferry outlines a simple architecture that should help you progress from a basic proof of concept to a minimal viable product without much hassle.

The microservices architectural pattern is an architectural style that is growing in popularity, given its flexibility and resilience. In this article, Toptal Freelance Python Developer Guilherme Caminha will focus on building a proof of concept microservices application in Python using Nameko, a microservices framework.

Computational photography is about enhancing the photographic process with computation. While we normally tend to think that this applies only to post-processing the end result (similar to photo editing), the possibilities are much richer since computation can be enabled at every step of the photographic process—starting with scene illumination. In this article, Toptal OpenCV Expert Radu Balaban walks us through two examples of computational photography: low light and high dynamic range.

Threading is just one of the many ways concurrent programs can be built. In this article, we will take a look at threading and a couple of other strategies in building concurrent programs in Python, as well as discuss how each is suitable in different scenarios.

As applications become more complex, having good logs can be very useful, not only when debugging but also to provide insight in application issue/performance. The Python standard library comes with a logging module that provides most of the basic logging features and is very handy but contains some quirks that can cause hours of headaches

While machine learning sounds highly technical, an introduction to the statistical methods involved quickly brings it within reach. In this article, Toptal Freelance Software Engineer Vladyslav Millier explores basic supervised machine learning algorithms and scikit-learn, using them to predict survival rates for Titanic passengers.

TensorFlow makes implementing deep learning on a production scale a breeze. However, understanding its core mechanisms and how dataflow graphs work is an essential step in leveraging the tool’s power. In this article, Toptal Freelance Software Engineer Oliver Holloway demonstrates how TensorFlow works by first solving a general numerical problem and then a deep learning problem.

Donald Knuth said that "premature optimization is the root of all evil." But there comes a time, usually in mature projects with high loads, when the need to optimize presents itself. In this article, Toptal Freelance Software Engineer Iulian Gulea talks about five common methods to optimize a web project’s code using principles that can be used in Django as well as other frameworks and languages. Using these principles, he demonstrates how to reduce the response time of a query from 77 to 3.7 seconds.

In this article, I will try to give you a good understanding of which scenarios could be covered by Celery. Not only will you see interesting examples, but will also learn how to apply Celery with real world tasks such as background mailing, report generation, logging and error reporting. I will share my own way of testing tasks beyond emulation and explain a few tricks that go beyond the official documentation and took me hours of research to discover myself.