List of Interview Questions BERT Interview Questions (NLP) In this article, we will go over various questions that cover the fundamentals and inner workings of the BERT model.
Natural Language Processing (NLP) NLP Project: Compare Text Summarization Models In this article, we will go over the basics of Text Summarization, the different approaches to generating automatic summaries, some of the real world applications of Text Summarization, and finally, we will compare various Text Summarization models with the help of ROUGE.
Natural Language Processing (NLP) Text Summarization Interview Questions (NLP) In this article, we will go over 70 questions that cover everything from the very basics of Text Summarization to the evaluation of summarized pieces of text using various metrics.
Computer Architecture GCC Compiler Intrinsics In this article, we will discuss the GNU Compiler Collection (GCC), the fundamentals of intrinsics, some of the ways in which these intrinsics can speed up vector code, and we will also take a look at a list of some of the x86 intrinsics that GCC offers.
Computer Architecture SIMD & SSE Instruction Set In this article, we will discuss scalar computing (and some of its drawbacks), the need for vector/parallel computing, the fundamental concepts behind single instruction, multiple data (or SIMD) architecture and SSE.
hardware AVX-512 In this article, we will discuss Intel's Advanced Vector Extensions 512 (AVX-512), which is an instruction set that was created to accelerate computational performance in areas such as artificial intelligence/deep learning.
Machine Learning (ML) Text Summarization using Transformers In this article, we will learn about the fundamentals of Text Summarization, some of the different ways in which we can summarize text, Transformers, the BART model, and finally, we will practically implement some of these concepts.
data science Fuzzy Relations, Propositions, Implications and Inferences In this article, we will first learn about fuzzy relations and the different types of operations that can be performed on them. Then, we will learn about the truth values of fuzzy propositions, about fuzzy implications or if-then rules.
data science Fuzzy Inference System: Introduction In this article, we will discuss a few fundamental concepts that govern the functioning of Fuzzy Systems. We will also discuss some of their real world applications while comparing and contrasting them to Crisp (Hard Computing) Systems.
Machine Learning (ML) Flattened Convolutional Neural Network In this article, we have explored the idea of Flattened Convolutional Neural Network and the problem of conventional CNN it solves.
Machine Learning (ML) Commonly Used Neural Networks We have explored the commonly used Neural Networks like Hebbian Neural Networks, Auto-Associative Neural Networks, Hopfield Neural Networks, Radial Basis Function Neural Networks and much more.