of the attention mechanism in different NLP problems, aiming to provide our readers with basic knowledge on this widely used method, discuss its different variants for different tasks, explore its association w
NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems,code simplify inside Jupyter Notebooks 100%. Table of contents Objective Original implementations are quite complex and not really beginner friendly. So I tried to simplify most of it. Also, there are...
NLU provides everything a data scientist might want to wish for in one line of code! 1000 + pre-trained models 100+ of the latest NLP word embeddings ( BERT, ELMO, ALBERT, XLNET, GLOVE, BIOBERT, ELECTRA, COVIDBERT) and different variations of them 50+ of the latest NLP sentence embedd...
We have benchmarks and competitions for almost every general area in AI [35], [36], [6], [37], [38], [39], such as planning, learning, game playing, deductive reasoning, and also for many particular areas such as machine translation, driving vehicles, chess, robotics. This has a ...
2.3. Pre-Training Model in NLP In the field of natural language processing (NLP), pre-trained models play a crucial role by enabling NLP models to achieve excellent performance without the need to train from scratch. Instead, these models can undergo fine-tuning directly on the pre-trained co...
Machine Translation- translating sentences from one language to another, best example would be Google translate. Information Translation- to take a text as input and represent it in a structured form like a database entries. 3. Hard or still need lot of work ...
(although advanced difficulty manipulation might help, see below). Therefore, in this study, we aim to investigate number processing (including early steps, such as understanding the semantic meaning of the numbers’ magnitudes, and potentially also the execution of a mathematical operation) in both...
For example, using string-based and semantic-based searches, a machine-aided mapping of ICD-9CM to SNOMED–CT through UMLS resulted in a 91% coverage, a 43% recall and a 27% precision [28]. However, it would appear that automated approaches alone are not adequate for all domains. For ...
This paper shows the importance of automated scoring (AS) and that it is better than human graders in terms of degree of reproducibility. Considering the potential of the automated scoring system, th...
Solving Math Word Problems (MWPs) automatically is a challenging task for AI-tutoring in online education. Most of the existing State-Of-The-Art (SOTA) neu