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Technical Guide

Discovering the Encoded Linguistic Knowledge in NLP Models

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This article is authored by Keyur Faldu and Dr. Amit Sheth. This article elaborates on a niche aspect of the broader cover story on “Rise of Modern NLP and the Need of Interpretability!”At Embibe, we desiderate answers to the open questions while we build the NLP platform to solve numerous problems for the academic content.Modern NLP models (BERT, GPT, … [Read more...] about Discovering the Encoded Linguistic Knowledge in NLP Models

Deep-Learning Based Object Detection in Crowded Scenes

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Object detection in crowded scenes is challenging. When objects gather, they tend to overlap largely with each other, leading to occlusions. Occlusion caused by objects of the same class is called intra-class occlusion, also referred to as crowd occlusion. Object detectors need to determine the locations of different objects in the crowd and accurately delineate their … [Read more...] about Deep-Learning Based Object Detection in Crowded Scenes

Transfer Learning for Time Series Forecasting and Classification

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A brief history: ImageNet was first published in 2009 and over the next four years would go on to form the bedrock of most computer vision models. To this day whether you are training a model to detect pneumonia or classify models of cars you will probably start with a model pre-trained on ImageNet or some other large (and general image) dataset.More recently papers … [Read more...] about Transfer Learning for Time Series Forecasting and Classification

NeurIPS 2020 Papers: Takeaways for a Deep Learning Engineer –  Computer Vision

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As mentioned in part 1– the most important thing:) – I went through all the titles of NeurIPS 2020 papers (more than 1900!) and read abstracts of 175 papers, and extracted DL engineer relevant insights from the following papers.This is part 2. See part 1 here.If this in-depth educational content is useful for you, you can subscribe to our AI research mailing list to be … [Read more...] about NeurIPS 2020 Papers: Takeaways for a Deep Learning Engineer –  Computer Vision

NeurIPS 2020 Papers: Takeaways for a Deep Learning Engineer

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Advances in Deep Learning research are of great utility for a Deep Learning engineer working on real-world problems as most of the Deep Learning research is empirical with validation of new techniques and theories done on datasets that closely resemble real-world datasets/tasks (ImageNet pre-trained weights are still useful!).But, churning a vast amount of … [Read more...] about NeurIPS 2020 Papers: Takeaways for a Deep Learning Engineer

Machine Learning on Knowledge Graphs at NeurIPS 2020

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NeurIPS is a major venue covering a wide range of ML & AI topics. Of course, there is something interesting for Graph ML aficionados and knowledge graph connoisseurs 🧐. Tune in to find out!This year, NeurIPS had 1900 accepted papers 😳 and 100+ among them are on graphs. Plus take into account several prominent workshops like KR2ML, DiffGeo4ML, and LMCA. Be sure to check … [Read more...] about Machine Learning on Knowledge Graphs at NeurIPS 2020

The Curious Case of Developmental BERTology

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This essay is written for machine learning researchers and neuroscientists (some jargons in both fields will be used). Though it is not intended to be a comprehensive review of literature, we will take a tour through a selection of classic work and new results from a range of topics, in an attempt to develop the following thesis:Just like the fruitful interaction between … [Read more...] about The Curious Case of Developmental BERTology

NeurIPS 2020: Key Research Papers in Natural Language Processing (NLP) & Conversational AI

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NeurIPS is the largest machine learning conference held every December. It brings together researchers in computational neuroscience, reinforcement learning, deep learning, and their applications such as computer vision, fairness and transparency, natural language processing, robotics, and more.Our team reviewed the papers accepted to NeurIPS 2020 and shortlisted the most … [Read more...] about NeurIPS 2020: Key Research Papers in Natural Language Processing (NLP) & Conversational AI

NeurIPS 2020: Key Research Papers in Computer Vision

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Our team reviewed the papers accepted to NeurIPS 2020 and shortlisted the most interesting ones across different research areas. Here are the topics we cover:Natural Language Processing & Conversational AIComputer VisionReinforcement Learning & MoreTackling COVID-19 with AI & Machine LearningIf you’re interested in the remarkable keynote presentations, … [Read more...] about NeurIPS 2020: Key Research Papers in Computer Vision

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