Agniva Maiti - OpenGenus IQ: Computing Expertise & Legacy

Inference process in Deep Learning [Complete Guide]

Inference is the process of applying trained models to new data for predictions. It plays a vital role in real-world applications, enabling insights, automation, and real-time responses.

Deep Learning

Training process of Deep Learning models

Deep learning has revolutionized artificial intelligence, helping machines to learn and make decisions autonomously like humans. The training process, vital for model generalization and performance, has been explored in this article at OpenGenus, along with variations across model types.

Deep Learning

Adam Optimizer

This article introduces the Adam optimizer, an adaptive algorithm widely used in machine learning and deep learning. It combines Adagrad and RMSprop, ensuring faster convergence and improved performance for various tasks like image classification, object detection etc.

Deep Learning

RMSprop (Root Mean Square Propagation)

RMSprop is a widely used ML optimization algorithm, adapting learning rates based on historical gradients. The article outlines its workings, advantages over traditional methods, discusses some drawbacks, and explores its current applications and future potential.

Data Structures

Swarm Intelligence for Distributed Data Structures

Distributed data systems provide a way of organising and managing data across interconnected computers or devices. It provides benefits such as scalability, fault tolerance and data synchronization.

Natural Language Processing (NLP)

Linguistic Data Mining and Corpus Linguistics

Linguistic Data Mining and Corpus Linguistics are two interrelated fields of computational linguistics that have gained significant attention in recent years. The article provides an overview of the key concepts and methods used in both, pros and cons and future prospects.