Unite.AI

JUNE 13, 2023

Then what we did was that we went back in time and said, “Let's pretend that I'm in 2010.” The way we did it is you started from a reinforcement learning perspective, we had a very good simulator of dynamics of the balloon, and then we also had this wind simulator.

Machine Learning 246

Machine Learning AI AI Algorithm 246

Viso.ai

MARCH 12, 2024

Today’s boom in computer vision (CV) started at the beginning of the 21 st century with the breakthrough of deep learning models and convolutional neural networks (CNN). proposed a deep convolutional neural network architecture codenamed Inception. Faster R-CNN as a single, unified network for object detection.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

TheSequence

DECEMBER 13, 2023

He holds a PhD in Theoretical Physics, was a 2010 Fulbright Scholar and has held research positions in Australia, the USA, and Switzerland. He has previously built machine learning-powered applications for start-ups and enterprises in the domains of natural language processing, topological data analysis, and time series.

LLM 64

LLM Natural Language Processing Machine Learning Deep Learning 64

O'Reilly Media

SEPTEMBER 19, 2023

And that brings our story to the present day: Stage 3: Neural networks High-end video games required high-end video cards. ” There’s as much Keras, TensorFlow, and Torch today as there was Hadoop back in 2010-2012. Those algorithms packaged with scikit-learn?

Algorithm 99

Algorithm Machine Learning Neural Network Data Scientist 99

AWS Machine Learning Blog

OCTOBER 10, 2023

The sample code supports horizontal and synchronous FL for training neural network models. She is also the recipient of the Best Paper Award at IEEE NetSoft 2016, IEEE ICC 2011, ONDM 2010, and IEEE GLOBECOM 2005. The ML framework used at FL clients is TensorFlow. Clients are compute nodes that perform local training.

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ML Algorithm Machine Learning Neural Network 92

ML Review

JUNE 4, 2018

The first paper, to the best of our knowledge, to apply neural networks to the image captioning problem was Kiros et al. These new approaches generally; Feed the image into a Convolutional Neural Network (CNN) for encoding, and run this encoding into a decoder Recurrent Neural Network (RNN) to generate an output sentence.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

AWS Machine Learning Blog

NOVEMBER 9, 2023

This leads to the same size and architecture as the original neural network. He received his PhD from University of Maryland, College Park in 2010. The basic idea is to design a low-rank matrix that is then added to the matrices with the original matrix weight of targeted layers of the model.

Natural Language Processing 82

Natural Language Processing NLP Large Language Models LLM 82

Flipboard

JULY 31, 2023

Nowadays, with the advent of deep learning and convolutional neural networks, this process can be automated, allowing the model to learn the most relevant features directly from the data. a convolutional neural network), which then learns to map the features of each image to its correct label.

Machine Learning 104

Machine Learning Computer Vision Deep Learning Convolutional Neural Networks 104

O'Reilly Media

JULY 25, 2023

To provide some coherence to the music, I decided to use Taylor Swift songs since her discography covers the time span of most papers that I typically read: Her main albums were released in 2006, 2008, 2010, 2012, 2014, 2017, 2019, 2020, and 2022. This choice also inspired me to call my project Swift Papers.

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ChatGPT UX Design AI Tools Metadata 98

Marek Rei

MARCH 14, 2022

I’ve heard plenty of stories about supervisors in the early 2010’s telling their students not to work on neural networks because ‘that field isn’t going anywhere’. In the worst case, you will learn something new. The supervisor wants what’s best for you, but they’re not all-knowing oracles.

NLP 40

NLP ML Neural Network Deep Learning 40

Viso.ai

DECEMBER 21, 2023

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries. Thus, positioning him as one of the top AI influencers in the world.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Towards AI

JULY 19, 2023

github.com Their core repos consist of SparseML: a toolkit that includes APIs, CLIs, scripts and libraries that apply optimization algorithms such as pruning and quantization to any neural network. Sparsify: a UI interface to optimize deep neural networks for better inference performance. Follow their code on GitHub.

NLP 95

NLP Neural Network Natural Language Processing Computer Vision 95

Towards AI

JULY 21, 2023

github.com Their core repos consist of SparseML: a toolkit that includes APIs, CLIs, scripts and libraries that apply optimization algorithms such as pruning and quantization to any neural network. Sparsify: a UI interface to optimize deep neural networks for better inference performance. Follow their code on GitHub.

NLP 52

NLP Neural Network Natural Language Processing Computer Vision 52