ELMo: Why it’s one of the biggest advancements in NLP. Embeddings from Language Models (ELMo) is a state-of-the-art language modeling idea. What makes it so successful?
Published in 2018, “Deep Contextualized Word Embeddings” presented the idea of Embeddings from Language Models (ELMo), which achieved state-of-the-art performance on many popular tasks including question-answering, sentiment analysis, and named-entity extraction. ELMo has been shown to yield performance improvements of up to almost 5%. But what makes this idea so revolutionary?
*What’s ELMo? *Not only is he a Muppet, but ELMo is also a powerful computational model that converts words into numbers. This vital process allows machine learning models (which take in numbers, not words, as inputs) to be trained on textual data.
Why is ELMo so good? There are a few primary points that stood out to me when I read through the original paper:
Let’s go through each of these points in detail and talk about why they’re important.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
Simple explanations of Artificial Intelligence, Machine Learning, and Deep Learning and how they’re all different
Artificial Intelligence (AI) will and is currently taking over an important role in our lives — not necessarily through intelligent robots.
Data Augmentation is a technique in Deep Learning which helps in adding value to our base dataset by adding the gathered information from various sources to improve the quality of data of an organisation.
In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics.