MachineLearning

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Architecting Effective Data Labeling Systems for Machine Learning Pipelines

Machine learning models are trained on massive datasets in which each data point is labeled to give it context and meaning. This deep dive describes how to build a data labeling architecture from scratch, with a focus on workflow, security, and data quality.

16 minute readContinue Reading
Reza Fazeli

Reza Fazeli

Theory, Tools, and Business Applications: An In-depth Look at Quantum Computing

Quantum computing is challenging the realities of technology, security, and industry as we know them. Here, we investigate the nuances of quantum mechanics and how to enter the world of quantum software development with tools such as Cirq and TensorFlow Quantum.

22 minute readContinue Reading
Joao Diogo de Oliveira

Joao Diogo de Oliveira

Advancing AI Image Labeling and Semantic Metadata Collection

Image labeling can be a tedious, time-consuming task, compounded by the sheer volume of data needed to train deep neural networks. This article breaks down large data set processing and explains how a new SaaS product can help automate image labeling.

13 minute readContinue Reading
Neven Pičuljan

Neven Pičuljan

In this ask-me-anything-style Q&A, leading Toptal AI developer Joao Diogo de Oliveira fields questions from fellow engineers about resources for pivoting to ML, approaches to large language models, and the most critical future applications of AI.

6 minute readContinue Reading
Joao Diogo de Oliveira

Joao Diogo de Oliveira

Ask an NLP Engineer: From GPT Models to the Ethics of AI

Want to expand your skills amid the current surge of revolutionary language models like GPT-4? In this ask-me-anything-style tutorial, Toptal data scientist and AI engineer Daniel Pérez Rubio fields questions from fellow programmers on a wide range of machine learning, natural language processing, and artificial intelligence topics.

10 minute readContinue Reading
Daniel Pérez Rubio

Daniel Pérez Rubio

Identifying the Unknown With Clustering Metrics

Clustering in machine learning has a variety of applications, but how do you know which algorithm is best suited to your data? Here’s how to amplify your data insights with comparison metrics, including the F-measure.

12 minute readContinue Reading
Surbhi Gupta

Surbhi Gupta

Ensemble Methods: The Kaggle Machine Learning Champion

Two heads are better than one. This proverb describes the concept behind ensemble methods in machine learning. Let’s examine why ensembles dominate ML competitions and what makes them so powerful.

9 minute readContinue Reading
Juan Manuel Ortiz de Zarate

Juan Manuel Ortiz de Zarate

Machine Learning Number Recognition: From Zero to Application

Harnessing the potential of machine learning for computer vision is not a new concept but recent advances and the availability of new tools and datasets have made it more accessible to developers.

In this article, Toptal Software Developer Teimur Gasanov demonstrates how you can create an app capable of identifying handwritten digits in under 30 minutes, including the API and UI.

10 minute readContinue Reading
Teimur Gasanov

Teimur Gasanov

Embeddings in Machine Learning: Making Complex Data Simple

Working with non-numerical data can be challenging, even for seasoned data scientists. To make good use of such data, it needs to be transformed. But how?

In this article, Toptal Data Scientist Yaroslav Kopotilov will introduce you to embeddings and demonstrate how they can be used to visualize complex data and make it usable.

11 minute readContinue Reading
Yaroslav Kopotilov

Yaroslav Kopotilov

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