Google Research AI blog

FEBRUARY 10, 2023

Robust algorithm design is the backbone of systems across Google, particularly for our ML and AI models. Google Research has been at the forefront of this effort, developing many innovations from privacy-safe recommendation systems to scalable solutions for large-scale ML. You can find other posts in the series here.)

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Algorithm Neural Network Auto-classification ML 110

Pickl AI

JANUARY 23, 2023

This framework can perform classification, regression, etc., but performs very well with neural networks. Keras supports a high-level neural network API written in Python. Deep Python integration makes it possible to easily create neural network layers in Python using well-known modules and packages.

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Machine Learning ML Neural Network Auto-classification 52

Unite.AI

DECEMBER 19, 2023

Most cybersecurity tools leverage machine learning (ML) models that present several shortcomings to security teams when it comes to preventing threats. ML solutions also require heavy human intervention and are trained on small data sets, exposing them to human bias and error. Like other AI and ML models, our model trains on data.

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Neural Network Deep Learning ML Metadata 144

Marktechpost

SEPTEMBER 13, 2024

In supervised image classification and self-supervised learning, there’s a trend towards using richer pointwise Bernoulli conditionals parameterized by sigmoid functions, moving away from output conditional categorical distributions typically parameterized by softmax. If you like our work, you will love our newsletter.

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Auto-classification Neural Network Machine Learning Computer Vision 104

Flipboard

APRIL 13, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses.

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Unite.AI

JUNE 24, 2024

MLOps , or Machine Learning Operations, is a multidisciplinary field that combines the principles of ML, software engineering, and DevOps practices to streamline the deployment, monitoring, and maintenance of ML models in production environments. What is MLOps?

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Data Drift Machine Learning Data Scientist ML 120

The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. Model monitoring and performance tracking : Platforms should include capabilities to monitor and track the performance of deployed ML models in real-time.

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Machine Learning Metadata Data Scientist Data Quality 134

Viso.ai

DECEMBER 3, 2023

Today, the most powerful image processing models are based on convolutional neural networks (CNNs). A popular library that uses neural networks for real-time human pose estimation in 3D, even for multi-person use cases, is named OpenPose. High-Resolution Net (HRNet) is a neural network for human pose estimation.

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Deep Learning Computer Vision Neural Network Robotics 98

Google Research AI blog

JANUARY 18, 2023

Language Models Computer Vision Multimodal Models Generative Models Responsible AI* Algorithms ML & Computer Systems Robotics Health General Science & Quantum Community Engagement * Other articles in the series will be linked as they are released. Top Computer Vision Computer vision continues to evolve and make rapid progress.

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Computer Vision Auto-classification Large Language Models Neural Network 132

ODSC - Open Data Science

APRIL 17, 2023

Finally, H2O AutoML has the ability to support a wide range of machine learning tasks such as regression, time-series forecasting, anomaly detection, and classification. Auto-ViML : Like PyCaret, Auto-ViML is an open-source machine learning library in Python. This makes Auto-ViML an ideal tool for beginners and experts alike.

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Data Science Auto-classification Machine Learning Data Scientist 59

AWS Machine Learning Blog

MARCH 28, 2024

You can deploy this solution with just a few clicks using Amazon SageMaker JumpStart , a fully managed platform that offers state-of-the-art foundation models for various use cases such as content writing, code generation, question answering, copywriting, summarization, classification, and information retrieval.

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LLM Auto-complete Auto-classification Generative AI 135

AWS Machine Learning Blog

JUNE 12, 2023

It can support a wide variety of use cases, including text classification, token classification, text generation, question and answering, entity extraction, summarization, sentiment analysis, and many more. GPT-J is an open-source 6-billion-parameter model released by Eleuther AI. 24xlarge, ml.g5.48xlarge, ml.p4d.24xlarge, 24xlarge.

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Deep Learning Auto-classification Computer Vision Machine Learning 91

ODSC - Open Data Science

OCTOBER 11, 2023

Even with the most advanced neural network architectures, if the training data is flawed, the model will suffer. In this post, I’ll give a high-level overview of how AI/ML can be used to automatically detect various issues common in real-world datasets. Machine learning models are only as good as the data they are trained on.

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Auto-classification Auto-complete Data Drift Machine Learning 52

Mlearning.ai

JUNE 22, 2023

Understanding the biggest neural network in Deep Learning Join 34K+ People and get the most important ideas in AI and Machine Learning delivered to your inbox for free here Deep learning with transformers has revolutionized the field of machine learning, offering various models with distinct features and capabilities.

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AWS Machine Learning Blog

AUGUST 8, 2023

These complex models often require hardware acceleration because it enables not only faster training but also faster inference when using deep neural networks in real-time applications. GPUs’ large number of parallel processing cores makes them well-suited for these DL tasks.

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BERT Deep Learning Auto-classification Python 97

AWS Machine Learning Blog

JANUARY 31, 2024

In the first part of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. The following screenshot illustrates the architecture of our Convolutional Neural Network (CNN) model.

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Computer Vision Auto-complete Deep Learning Auto-classification 118

The MLOps Blog

APRIL 20, 2023

Learn more → Best MLOps Tools For Your Computer Vision Project Pipeline → Building MLOps Pipeline for Computer Vision: Image Classification Task [Tutorial] Fine-tuning Model fine-tuning and Transfer Learning have become essential techniques in my workflow when working with CV models. Libraries like imgaug , albumentations , and torchvision.

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Computer Vision Auto-classification Neural Network Convolutional Neural Networks 64

Snorkel AI

FEBRUARY 2, 2023

If you’re not familiar with the Snorkel Flow platform, the iteration loop looks like this: Label programmatically: Encode labeling rationale as labeling functions (LFs) that the platform uses as sources of weak supervision to intelligently auto-label training data at scale. Auto-generated tag-based LFs. Streamlined tagging workflows.

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Auto-classification Software Engineer Neural Network Machine Learning 52

Snorkel AI

FEBRUARY 2, 2023

If you’re not familiar with the Snorkel Flow platform, the iteration loop looks like this: Label programmatically: Encode labeling rationale as labeling functions (LFs) that the platform uses as sources of weak supervision to intelligently auto-label training data at scale. Auto-generated tag-based LFs. Streamlined tagging workflows.

Auto-classification 52

Auto-classification Software Engineer Neural Network Machine Learning 52

Mlearning.ai

MAY 23, 2023

Let us first understand the meaning of bias and variance in detail: Bias: It is a kind of error in a machine learning model when an ML Algorithm is oversimplified. It is introduced into an ML Model when an ML algorithm is made highly complex. Classification is very important in machine learning. Explain it’s working.

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Data Science Neural Network Deep Learning Machine Learning 52

Dlabs.ai

JANUARY 16, 2023

This article will walk you through how to process large medical images efficiently using Apache Beam — and we’ll use a specific example to explore the following: How to approach using huge images in ML/AI Different libraries for dealing with said images How to create efficient parallel processing pipelines Ready for some serious knowledge-sharing?

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Neural Network ML Auto-classification Convolutional Neural Networks 52

Mlearning.ai

JUNE 28, 2023

This is the link [8] to the article about this Zero-Shot Classification NLP. BART stands for Bidirectional and Auto-Regression, and is used in processing human languages that is related to sentences and text. The approach was proposed by Yin et al. The technology that is used in this program is called BART.

Machine Learning 52

Machine Learning NLP Auto-classification Natural Language Processing 52

AWS Machine Learning Blog

NOVEMBER 30, 2023

Amazon SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate machine learning (ML) predictions for their business needs. Neural network torch: A neural network model that’s implemented using Pytorch. Otherwise, it chooses ensemble mode.

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Machine Learning Neural Network Algorithm Auto-classification 117

Mlearning.ai

MAY 8, 2023

Artificial Neural Networks are an example of biological-inspired models. About this series In this series , we will learn how to code the must-to-know deep learning algorithms such as convolutions, backpropagation, activation functions, optimizers, deep neural networks, and so on using only plain and modern C++.

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Deep Learning Auto-classification Neural Network Machine Learning 52