The world of NLP already contains an assortment of pre-trained models and techniques. This article discusses how to best discern which model will work for your goals.

Is it possible to use machine learning with small data? Yes, it is! Here's N-Shot Learning.

The Gated Recurrent Unit (GRU) is the newer version version of the more popular LSTM. Let's unveil this network and explore the differences between these 2 siblings.

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Getting sufficient clean, reliable data is one of the hardest parts of data science. Web scraping automates the process of visiting web pages, downloading the data, and cleaning the results. With this technique, we can create new datasets from a large compendium of web pages.

This article gives the readers a checklist to structure their machine learning (applies to deep ones too) projects in effective ways.

The article elucidates the importance of statistics in the field of data science, wherein "Statistics" is imagined as a friend to a data scientist and their friendship is unraveled.

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Genetic algorithms are a specific approach to optimization problems that can estimate known solutions and simulate evolutionary behavior in complex systems.

Generative adversarial networks (GANs) have been the go-to state of the art algorithm to image generation in the last few years. In this article, you will learn about the most significant breakthroughs in this field, including BigGAN, StyleGAN, and many more.