![]() Some of the greatest applications of recurrent networks are machine translation and time series data modeling. Recurrent networks employ the encoder-decoder architecture, and we mainly use them when dealing with tasks where both the input and outputs are sequences in some defined ordering. ![]() Recurrent Network - the shining era before Transformersīefore diving into the core concept of transformers, let’s briefly understand what recurrent models are and their limitations. Then, we will walk you through some real-world case scenarios using Huggingface transformers. After explaining their benefits compared to recurrent neural networks, we will build your understanding of Transformers. ![]() This conceptual blog aims to cover Transformers, one of the most powerful models ever created in Natural Language Processing. Language translation is another great application because it allows us to overcome communication barriers.Medical field researchers use NLP to pave the way for faster drug discovery.Apple’s Siri personal assistant, which can help users in their day-to-day activities such as setting alarms, texting, answering questions, etc.Below are some of the examples of Natural Language Processing in practice: ![]() The extensive contribution of researchers in NLP, short for Natural Language Processing, during the last decades has been generating innovative results in different domains. ![]()
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