Machine Learning (ML) Xception: Deep Learning with Depth-wise Separable Convolutions Xception is a deep convolutional neural network architecture that involves Depthwise Separable Convolutions. This network was introduced Francois Chollet who works at Google, Inc.
Machine Learning (ML) ELMo: Deep contextualized word representations ELMo is the state-of-the-art NLP model that was developed by researchers at Paul G. Allen School of Computer Science & Engineering, University of Washington. In this article, we will go through ELMo in depth and understand its working.
Machine Learning (ML) BERT base vs BERT large BERT base model has 12 encoder layers stacked on top of each other whereas BERT large has 24 layers of encoders stacked on top of each other.
Machine Learning (ML) ALBERT (A Lite BERT) NLP model ALBERT stands for A Lite BERT and is a modified version of BERT NLP model. It builds on three key points such as Parameter Sharing, Embedding Factorization and Sentence Order Prediction (SOP).
Machine Learning (ML) RoBERTa: Robustly Optimized BERT pre-training Approach RoBERTa (Robustly Optimized BERT pre-training Approach) is a NLP model and is the modified version (by Facebook) of the popular NLP model, BERT. It is more like an approach better train and optimize BERT (Bidirectional Encoder Representations from Transformers).
Machine Learning (ML) Introduction to GPT models Generative Pre-Training (GPT) models are trained on unlabeled dataset (which are available in abundance). There are different variants like GPT-1, GPT-2 and GPT-3 which we have explored.
Machine Learning (ML) BERT and SEARCH: How BERT is used to improve searching? In this article, we have explored how BERT model can be used to improve search results in search engines like Google Search, Bing and others.
Machine Learning (ML) Introduction to Multilingual BERT (M-BERT) We explored what is Multilingual BERT (M-BERT) and see a general introduction of this NLP model.
Machine Learning (ML) A Deep Learning Approach for Native Language Identification (NLI) Native language identification (NLI) is the task of determining an author's native language based only on their writings or speeches in a second language. In this article, we will implement a model to identify native language of the author.
Machine Learning (ML) Native Language Identification (NLI) Native language identification (NLI) is the task of determining an author's native language based only on their writings or speeches in a second language. This is an application of Machine Learning.
Machine Learning (ML) An Introduction to Recommendation System This is the introduction to recommendation systems, how it works and more. We have different approaches to it like Content-based systems, Collaborative filtering systems and Hybrid systems.
