Anirudh Edpuganti - OpenGenus IQ: Computing Expertise & Legacy

6 Uses of Deep Learning in Laptops

Deep Learning, a powerful offshoot of machine learning and artificial intelligence, has been revolutionizing multiple industries, with laptops being one of them. This article at OpenGenus explores profound applications of deep learning in laptops, enhancing our interactions with these vital devices.

Deep Learning

5 uses of Deep Learning for Media: A Revolution in Content Creation

This article at OpenGenus delves into how deep learning is being applied in the media industry, revolutionizing the way we create, consume, and interact with media content.

Culture

Entrepreneurship: From Classroom to Boardroom

Every thriving business starts from a seed - an idea. As a student, the moment this seed takes root can be exhilarating, yet equally daunting. The thrill lies in the potential to effect change, to disrupt the status quo and make a difference.

Deep Learning

Global Temperature Change Prediction using ML and DL

This article at OpenGenus explores how ML and DL can be effectively utilized for global temperature change prediction.

Machine Learning (ML)

Tuning Your AI: The Emergent Field of Prompt Engineering

Prompt engineering is an exciting and rapidly evolving field in the world of artificial intelligence (AI). It is the process of designing, testing, and optimizing inputs, or "prompts," to instruct AI models to generate desired outputs.

Machine Learning (ML)

Dynamic Mode Decomposition (DMD): An Overview of the Mathematical Technique and Its Applications

Dynamic Mode Decomposition (DMD) is a data-driven method used to analyze and extract dynamic behavior from high-dimensional data sets. It is a powerful tool for studying fluid dynamics, image processing, and other complex systems.

Machine Learning (ML)

Exploration-Exploitation Dilemma

The exploration-exploitation dilemma is a concept that describes the challenge of deciding between exploring new options or exploiting already known options to maximize rewards.

Reinforcement Learning (RL)

50+ Reinforcement Learning Key Terms: Understanding the Language of RL

In this article, we have covered 50+ Key Terms in the domain of Reinforcement Learning. This will give a strong hold on RL.

Deep Learning

Policy Gradient in RL

Policy gradient is a popular approach in RL that is used to learn a policy function that maps states to actions, by directly optimizing the expected return of the policy.

Deep Learning

Resilient Backpropagation (Rprop): The Robust Optimization Algorithm for Training Deep Neural Networks

Resilient Backpropagation (Rprop) is a popular optimization algorithm used in training artificial neural networks. The algorithm was first introduced by Martin Riedmiller and Heinrich Braun in 1993.

Deep Learning

Layer Normalization: An Essential Technique for Deep Learning Beginners

Layer normalization is a relatively new technique in the field of deep learning. It was first introduced by Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey Hinton in their 2016 paper "Layer Normalization".

Deep Learning

Multi-Layer Perceptron (MLP): A Basic Understanding

Multi Layer Perceptron (MLP) is a type of artificial neural network that is widely used for various machine learning tasks such as classification and regression. It is called a multi-layered perceptron because it has many layers of nodes (known as artificial neurons) that connect to each other.