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Agniva Maiti

Agniva Maiti

Hi! I'm Agniva, an aspiring data scientist with a love for languages and coffee. I'm currently in my 2nd year of B.Tech (CSE) in KIIT, Odisha, India. I'm also interested in Web and App Development.

Dimapur, Nagaland •
11 posts •
Machine Learning (ML)

Genre Classification through Song Lyrics

This article presents a practical implementation of music genre classification using song lyrics and machine learning algorithms. By leveraging NLP techniques and logistic regression, it demonstrates efficient categorization of songs, offering insights for music analysis and recommendation systems.

Agniva Maiti Agniva Maiti
Natural Language Processing (NLP)

Interview questions on NLP

Natural language processing may be used to query the data using voice or text in natural language.

Agniva Maiti Agniva Maiti
Machine Learning (ML)

Sentiment Analysis For Mental Health Sites and Forums

This OpenGenus article delves into the crucial role of sentiment analysis in understanding emotions on mental health platforms. Featuring a Python program using NLTK's VADER, it explains the importance of comprehending user emotions for early intervention and personalized user experiences.

Agniva Maiti Agniva Maiti
Machine Learning (ML)

ML model to predict Waiter’s Tip

This OpenGenus article explores the application of machine learning techniques in predicting waiter tips based on factors such as total bill, day and time. Written in Python, the code employs one-hot encoding and Linear Regression, offering an understanding of these concepts.

Agniva Maiti Agniva Maiti
Deep Learning

MobileNet V3 model

MobileNetV3 is a neural network architecture designed to provide efficient deep learning capabilities on resource-constrained mobile devices. We delve into the essence of MobileNetV3, exploring its history, applications, advantages, disadvantages, and underlying architecture.

Agniva Maiti Agniva Maiti
Deep Learning

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.

Agniva Maiti Agniva Maiti
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.

Agniva Maiti Agniva Maiti
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.

Agniva Maiti Agniva Maiti
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.

Agniva Maiti Agniva Maiti
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.

Agniva Maiti Agniva Maiti
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.

Agniva Maiti Agniva Maiti
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