Python

Showing 19-27 of 58 results
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Python Logging: An In-Depth Tutorial

by Son Nguyen Kim

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

6 minute readContinue Reading
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Exploring Supervised Machine Learning Algorithms

by Vlad Miller

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.

24 minute readContinue Reading
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Getting Started with TensorFlow: A Machine Learning Tutorial

by Dino Causevic

TensorFlow is more than just a machine intelligence framework. It is packed with features and tools that make developing and debugging machine learning systems easier than ever. In this article, Toptal Freelance Software Engineer Dino Causevic gives us an overview of TensorFlow and some auxiliary libraries to debug, visualize, and tweak the models created with it.

19 minute readContinue Reading
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From Solving Equations to Deep Learning: A TensorFlow Python Tutorial

by Oliver Holloway

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.

10 minute readContinue Reading
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Create Data from Random Noise with Generative Adversarial Networks

by Cody Nash

Generative adversarial networks, among the most important machine learning breakthroughs of recent times, allow you to generate useful data from random noise. Instead of training one neural network with millions of data points, you let two neural networks contest with each other to figure things out. In this article, Toptal Freelance Software Engineer Cody Nash gives us an overview of how GANs work and how this class of machine learning algorithms can be used to generate data in data-limited situations.

13 minute readContinue Reading
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A Guide to Performance Testing and Optimization With Python and Django

by Iulian Gulea

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.

12 minute readContinue Reading
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Maximum Flow and the Linear Assignment Problem

by Dmitri Ivanovich Arkhipov

The Hungarian graph algorithm solves the linear assignment problem in polynomial time. By modeling resources (e.g., contractors and available contracts) as a graph, the Hungarian algorithm can be used to efficiently determine an optimum way of allocating resources.

25+ minute readContinue Reading
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Orchestrating a Background Job Workflow in Celery for Python

by Rustem Kamun

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.

15 minute readContinue Reading
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How to Build an Email Sentiment Analysis Bot: An NLP Tutorial

by Shanglun Wang

Build a bot that analyzes the sentiment of incoming email messages using Recursive Neural Tensor Networks from the Stanford NLP library.

10 minute readContinue Reading

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