Neural Architecture Search NAS - Learn Data Science with Travis

Neural-Architecture-Search-NAS

Neural Architecture Search (NAS) is an innovative approach in machine learning that automates the design of neural network architectures. By treating the architecture design process as an optimization problem, NAS aims to discover optimal configurations that enhance model performance without extensive human intervention. This method leverages various search strategies, including reinforcement learning, evolutionary algorithms, and gradient-based techniques, to explore a vast search space of potential architectures. As a result, NAS significantly reduces the time and resources required for model development, making it a valuable tool in advancing deep learning applications across diverse fields such as image recognition and natural language processing.

The Fundamentals of Neural Architecture Search (NAS)

Towards AI

Neural Architecture Search (NAS) has become a popular subject in the area of machine-learning science. Commercial services such as Google’s AutoML and open-source libraries such as Auto-Keras [1]…

Beyond Human Intuition: An Introduction to Neural Architecture Search (NAS)

Level Up Coding

Member-only story Beyond Human Intuition: An Introduction to Neural Architecture Search (NAS) Explore primary search strategies of NAS and its practical applications to optimizing complex architecture...

The Evolved Transformer — Enhancing Transformer with Neural Architecture Search

Towards Data Science

Neural architecture search (NAS) is the process of algorithmically searching for new designs of neural networks. Though researchers have developed sophisticated architectures over the years, the…

An overview on MnasNet: Platform-Aware Neural Architecture Search for Mobile

Analytics Vidhya

Neural Architecture Search is the task of automatically finding efficient neural network architectures using learning algorithms and deep-learning. Reinforcement learning-based methods are often used…...

🔪 Edge#67: Dissecting Neural Architecture Search in the context of AutoML

TheSequence

In this issue: we dissect Neural Architecture Search (NAS) in the context of automated machine learning (AutoML); we explain Microsoft’s Project Petridish, a new type of NAS algorithm that can produce...

Hierarchical Neural Architecture Search

Towards Data Science

Many researchers and developers are interested in what Neural Architecture Search can offer their Deep Learning models, but are deterred by monstrous computational costs. Many techniques have been…