×
Home Discussions Write at Opengenus IQ
×
  • About
  • Track your progress
  • Deep Learning Projects
  • Python Projects
  • Join our Internship 🎓
  • RANDOM
  • 100+ Graph Algorithms
  • 100+ DP Problems
  • 50+ Linked List Problems
  • 50+ Array Problems
  • One Liner
  • 50+ Binary Tree problems
  • Home
  • Rust Projects
B E Pranav Kumaar

B E Pranav Kumaar

B E Pranav Kumaar is a Machine Learning Developer, Intern at OpenGenus and is pursuing B. Tech in Computer Science Engineering and AI from Amrita Vishwa Vidyapeetham (2020 to 2024).

Bangalore Urban, Karnataka, India •
11 posts •
Machine Learning (ML)

Feature Selector Using LASSO

A technique for reducing the dimensionality of machine learning datasets is the Feature Selector. The selection process of the Feature Selector is based on a logically accurate measurement that determines the importance of each feature present in the data.

B E Pranav Kumaar B E Pranav Kumaar
Software Engineering

Interview Questions on MatLab

In this article, we have presented the most important Interview Questions on MatLab along with detailed answers.

B E Pranav Kumaar B E Pranav Kumaar
Machine Learning (ML)

Huber Fitting using ADMM

Huber Fitting in general is the approach of using the Huber function to fit the data models, the advantage of this approach is due to the clever formulation of the Huber function which brilliantly combines the best features of both preceding optimization solution approaches of LAD and LS.

B E Pranav Kumaar B E Pranav Kumaar
Machine Learning (ML)

LASSO using ADMM

LASSO is the acronym for Least Absolute Shrinkage and Selection Operator. Regression models' predictability and interpretability were enhanced with the introduction of Lasso.

B E Pranav Kumaar B E Pranav Kumaar
Machine Learning (ML)

Least Absolute Deviation using ADMM

Least Absolute Deviation (LAD) is a powerful approach for solving optimization problems with good tolerance to outliers. Hence solving it to obtain a practicably applicable form is essential to take advantage of its theoretical prowess.

B E Pranav Kumaar B E Pranav Kumaar
Machine Learning (ML)

ADMM - Alternating Direction Method of Multipliers

Distributed convex optimization, and in particular, large-scale issues occurring in statistics, machine learning, and related fields, are particularly suited to the Alternating Direction Method of Multipliers (ADMM).

B E Pranav Kumaar B E Pranav Kumaar
Machine Learning (ML)

Drone simulation with object detection

Drones are Unmanned Aerial Vehicles (UAV) that are remotely controlled either by humans or by computer programs. They range in size from under one pound to several hundred pounds.

B E Pranav Kumaar B E Pranav Kumaar
Machine Learning (ML)

Panoptic Segmentation

Panoptic Segmentation is an improved human-like image processing approach that combines the goals of both Instance and Semantic Segmentation. It was first proposed in a 2018 paper by Alexander Kirillov.

B E Pranav Kumaar B E Pranav Kumaar
Machine Learning (ML)

Grouped and Shuffled Grouped Convolution

In this article, we have explored the variant of Convolution named Grouped and Shuffled Grouped Convolution.

B E Pranav Kumaar B E Pranav Kumaar
Machine Learning (ML)

RefineNet Model

In this article, we have explained RefineNet Model in depth which is a deep learning model used for Semantic Segmentation.

B E Pranav Kumaar B E Pranav Kumaar
clustering algorithm

Spectral Clustering

Spectral clustering is an interesting Unsupervised clustering algorithm that is capable of correctly clustering Non-convex data by the use of clever Linear algebra.

B E Pranav Kumaar B E Pranav Kumaar
OpenGenus IQ © 2023 All rights reserved â„¢ [email: team@opengenus.org]
Top Posts LinkedIn Twitter