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.

Machine learning and artificial intelligence are popular topics, vast domains with multiple paradigms to solve any given challenge. In this article, Toptal Machine Learning Expert Adam Stelmaszczyk walks us through implementing deep Q-learning, a fundamental algorithm in the AI/ML world, with modern libraries such as TensorFlow, TensorBoard, Keras, and OpenAI Gym.

The modern, cross-platform programming language Haxe is well-known in some circles, yet many developers have never heard of it. Since it first appeared in 2005, it's been battle-tested by its loyal—if rather quiet—following. In this article, Toptal Freelance Software Engineer Kevin Bloch explores the Haxe ecosystem and how to transpile some sample code.

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.

Deep learning has proven its power across many domains, from beating humans at complex board games to synthesizing music. It has also been used extensively in natural language processing. In this article, Toptal Freelance Software Engineer Shanglun (Sean) Wang shows how easy it is to build a text classification program using different techniques and how well they perform against each other.

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.