MachineLearning

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Surbhi Gupta

Identifying the Unknown With Clustering Metrics

By Surbhi Gupta
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.
13 minute readContinue Reading
Juan Manuel Ortiz de Zarate

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
Teimur Gasanov

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
Yaroslav Kopotilov

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
Alan Reiner

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
Nauman Mustafa

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
Emmanuel Tsukerman

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
Juan Manuel Ortiz de Zarate

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
Urwa Muaz

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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