MachineLearning

Showing 1-9 of 28 results
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Ensemble Methods: The Kaggle Machine Learning Champion

by Juan Manuel Ortiz de Zarate

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
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Machine Learning Number Recognition - From Zero to Application

by Teimur Gasanov

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
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Embeddings in Machine Learning: Making Complex Data Simple

by Yaroslav Kopotilov

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
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The Many Applications of Gradient Descent in TensorFlow

by Alan Reiner

TensorFlow is one of the leading tools for training deep learning models. Outside that space, it may seem intimidating and unnecessary, but it has many creative uses—like producing highly effective adversarial input for black-box AI systems.

18 minute readContinue Reading
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Getting the Most Out of Pre-trained Models

by Nauman Mustafa

Pre-trained models are making waves in the deep learning world. Using massive pre-training datasets, these NLP models bring previously unheard-of feats of AI within the reach of app developers.

10 minute readContinue Reading
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Sound Logic and Monotonic AI Models

by Emmanuel Tsukerman

For those working with AI, the future is certainly exciting. At the same time, there is a general sense that AI suffers from one pesky flaw: AI in its current state can be unpredictably unreliable.

12 minute readContinue Reading
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Stars Realigned: Improving the IMDb Rating System

by Juan Manuel Ortiz de Zarate

IMDb ratings have genre bias: For example, dramas tend to score higher. Removing common feature bias and keeping unique characteristics, it's possible to create a new, refined score based on IMDb information.

10 minute readContinue Reading
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Semi-supervised Image Classification With Unlabeled Data

by Urwa Muaz

Supervised learning is the key to computer vision and deep learning. However, what happens when you don’t have access to large, human-labeled datasets? In this article, Toptal Computer Vision Developer Urwa Muaz demonstrates the potential of semi-supervised image classification using unlabeled datasets.

9 minute readContinue Reading
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Accelerate with BERT: NLP Optimization Models

by Jesse Moore

For a successful natural language processing project, collecting and preparing data, building resilient pipelines, and getting "model ready" can easily take months of effort even with the most talented engineers. But what if we could reduce the data required to a fraction? In this article, we’ll cover how transfer learning is making world-class models open source and introduce BERT (bidirectional encoder representations from transformers). BERT is the most powerful NLP “tool” to date. We’ll explore how it works and why it will change the way companies execute NLP projects.

6 minute readContinue Reading

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