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Neural Architecture Search with NNI

Towards Data Science

We use an AutoML tool Neural Network Intelligence (NNI) to do neural architecture search. We build a neural network to solve a function approximation problem and use NNI to optimize the network.

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]…

🔎🔍 Edge#69: Search Strategies in Neural Architecture Search

TheSequence

In this issue: we explore the search strategies in neural architecture search; we learn about Google’s evolved transformer that is a killer combination of transformers and NAS; we discuss Microsoft’s ...

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…

Neural Architecture Search (NAS)- The Future of Deep Learning

Towards Data Science

Most of us have probably heard about the success of ResNet, winner of ILSVRC 2015 in image classification, detection, and localization and Winner of MS COCO 2015 detection, and segmentation. It is an…...

Neural Architecture Search — Limitations and Extensions

Towards Data Science

For the past couple of years, researchers and companies have been trying to make deep learning more accessible to non-experts by providing access to pre-trained computer vision or machine translation…...

Illustrated: Efficient Neural Architecture Search

Towards Data Science

A tutorial on ENAS to generate neural networks using the macro and micro search strategies. This tutorial has illustrations and animations so that readers can better understand the concepts.

Neural Architecture Search (NAS) and Reinforcement Learning (RL)

Towards AI

Computer vision, and more specifically in classification tasks, are among the most popular deep learning techniques. Convolution Neural Network (CNN) particularly popular in the computer vision field…...

Neural Architecture Search: a model creation company

Towards Data Science

When I was learning and get my hands dirty in machine learning, I always wondered how Google AutoML was able to pick up a suitable model for a given task, returning promising and encouraging metric…

Edge#4: Beauty of Neural Architecture Search, and Uber's Ludwig that needs no code

TheSequence

In this issue: we look at Neural Architecture Search (NAS) that is equal to or outperform hand-designed architectures; we explain the research paper “A Survey on Neural Architecture Search” and how it...

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...