PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. This ensures that the population remains employable and beneficial to the country.

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Google Research AI blog

FEBRUARY 23, 2023

Commensurate with our mission to demonstrate these societal benefits , Google Research’s programs in applied machine learning (ML) have helped place Alphabet among the top five most impactful corporate research institutions in the health and life sciences publications on the Nature Impact Index in every year from 2019 through 2022.

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Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Convolutional neural networks (CNNs) can learn complicated patterns and features from enormous datasets, emulating the human visual system. Convolutional Neural Networks (CNNs) Deep learning in medical image analysis relies on CNNs.

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Google Research AI blog

FEBRUARY 2, 2023

Great machine learning (ML) research requires great systems. In this post, we provide an overview of the numerous advances made across Google this past year in systems for ML that enable us to support the serving and training of complex models while easing the complexity of implementation for end users.

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Dataconomy

AUGUST 22, 2024

Aleksandr Timashov is an ML Engineer with over a decade of experience in AI and Machine Learning. On these projects, I mentored numerous ML engineers, fostering a culture of innovation within Petronas. You told us you were implementing these projects in 2020-2022, so it all started amid the Covid-19 times.

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Google Research AI blog

FEBRUARY 21, 2023

With the amazing advances in machine learning (ML) and quantum computing, we now have powerful new tools that enable us to act on our curiosity, collaborate in new ways, and radically accelerate progress toward breakthrough scientific discoveries. You can find other posts in the series here.)

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Heartbeat

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

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Towards AI

NOVEMBER 16, 2024

In particular, min-max optimisation is curcial for GANs [2], statistics, online learning [6], deep learning, and distributed computing [7]. Vladu, “Towards deep learning models resistant to adversarial attacks,” arXivpreprint arXiv:1706.06083, 2017.[5] 7659–7679, 2022.[16] Arjovsky, S. Chintala, and L.

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PyImageSearch

DECEMBER 11, 2023

Kicking Off with a Keynote The second day of the Google Machine Learning Community Summit began with an inspiring keynote session by Soonson Kwon, the ML Community Lead at Google. The focus of his presentation was clear and forward-thinking: Accelerate AI/ML research and application.

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PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate.

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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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Heartbeat

FEBRUARY 28, 2023

The past few years have witnessed exponential growth in medical image analysis using deep learning. In this article we will look into medical image segmentation and see how deep learning can be helpful in these cases. This can be further classified as supervised and unsupervised learning. Image by author.

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Google Research AI blog

FEBRUARY 28, 2023

Adherence to such public health programs is a prevalent challenge, so researchers from Google Research and the Indian Institute of Technology, Madras worked with ARMMAN to design an ML system that alerts healthcare providers about participants at risk of dropping out of the health information program. certainty when used correctly.

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Google Research AI blog

FEBRUARY 14, 2023

As we do this, we’re transforming robot learning into a scalable data problem so that we can scale learning of generalized low-level skills, like manipulation. In this blog post, we’ll review key learnings and themes from our explorations in 2022.

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Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

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AWS Machine Learning Blog

OCTOBER 26, 2023

Intuitivo, a pioneer in retail innovation, is revolutionizing shopping with its cloud-based AI and machine learning (AI/ML) transactional processing system. Our AI/ML research team focuses on identifying the best computer vision (CV) models for our system. Inferentia has been shown to reduce inference costs significantly.

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Dataversity

DECEMBER 16, 2022

2022 was a big year for AI, and we’ve seen significant advancements in various areas – including natural language processing (NLP), machine learning (ML), and deep learning. Unsupervised and self-supervised learning are making ML more accessible by lowering the training data requirements.

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AWS Machine Learning Blog

APRIL 19, 2023

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. We recently developed four more new models.

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Towards AI

JULY 19, 2023

How to Maximize ML Project Success with Efficient Scoping? | In Aug 2022, Forbes stated that somewhere between 60–80% of AI projects are failing, according to different sources. This shows that scoping the projects is one of the most important steps before starting a machine learning project. General Outline for Scoping.

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The MLOps Blog

AUGUST 11, 2023

There comes a time when every ML practitioner realizes that training a model in Jupyter Notebook is just one small part of the entire project. At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. What are ML pipeline architecture design patterns?

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Dataconomy

FEBRUARY 26, 2024

GPUs: The versatile powerhouses Graphics Processing Units, or GPUs, have transcended their initial design purpose of rendering video game graphics to become key elements of Artificial Intelligence (AI) and Machine Learning (ML) efforts.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Developing NLP tools isn’t so straightforward, and requires a lot of background knowledge in machine & deep learning, among others.

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Towards AI

AUGUST 25, 2023

How to get started with an AI project Vackground on Unsplash Background Here I am assuming that you have read my previous article on How to Learn AI. Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed.

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AWS Machine Learning Blog

MAY 31, 2023

Running machine learning (ML) workloads with containers is becoming a common practice. What you get is an ML development environment that is consistent and portable. In this post, we show you how to run your ML training jobs in a container using Amazon ECS to deploy, manage, and scale your ML workload.

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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AWS Machine Learning Blog

JUNE 22, 2023

Light & Wonder teamed up with the Amazon ML Solutions Lab to use events data streamed from LnW Connect to enable machine learning (ML)-powered predictive maintenance for slot machines. Predictive maintenance is a common ML use case for businesses with physical equipment or machinery assets.

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Mlearning.ai

JULY 6, 2023

NOTES, DEEP LEARNING, REMOTE SENSING, ADVANCED METHODS, SELF-SUPERVISED LEARNING A note of the paper I have read Photo by Kelly Sikkema on Unsplash Hi everyone, In today’s story, I would share notes I took from 32 pages of Wang et al., 2022’s paper. 2022 Deep learning notoriously needs a lot of data in training.

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ODSC - Open Data Science

SEPTEMBER 21, 2023

Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business. Machine learning is ideal for cases when you want to do a semi-routine task faster, with more accuracy, or at a far larger scale than is possible with other solutions.

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

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Heartbeat

JANUARY 11, 2023

The beginning of 2023 brings with it a shift in focus for Heartbeat and we’re excited to dive deeper into Comet related tutorials, more deep learning content, and some NLP and computer vision projects. Submissions are once again open and you can learn more on our Call for Contributors page.

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AWS Machine Learning Blog

APRIL 12, 2023

They’ve built a deep-learning model ScarceGAN, which focuses on identification of extremely rare or scarce samples from multi-dimensional longitudinal telemetry data with small and weak labels. This work has been published in CIKM’21 and is open source for rare class identification for any longitudinal telemetry data.

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Applied Data Science

AUGUST 2, 2021

Big Ideas What to look out for in 2022 1. They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. Give this technique a try to take your team’s ML modelling to the next level.

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AWS Machine Learning Blog

AUGUST 2, 2024

GraphStorm is a low-code enterprise graph machine learning (GML) framework to build, train, and deploy graph ML solutions on complex enterprise-scale graphs in days instead of months. introduces refactored graph ML pipeline APIs. Based on customer feedback for the experimental APIs we released in GraphStorm 0.2, GraphStorm 0.3

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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ODSC - Open Data Science

MARCH 22, 2023

billion in 2022, an increase of 21.3% Nevertheless, we are still left with the question: How can we do machine learning better? To find out, we’ve taken some of the upcoming tutorials and workshops from ODSC East 2023 and let the experts via their topics guide us toward building better machine learning.

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Mlearning.ai

AUGUST 7, 2023

Introduction Training deep learning models is a heavy task from computation and memory requirement perspective. Motivation and proposed mechanism Training phase of deep learning models exhibit varied sensitivity to the amount of system resources (CPU cores, system memory or DRAM). Reference [ 1 ] Mohan, Jayashree, et al.

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Smart Data Collective

JUNE 22, 2023

Taking the world by storm, artificial intelligence and machine learning software are changing the landscape in many fields. Earlier today, one analysis found that the market size for deep learning was worth $51 billion in 2022 and it will grow to be worth $1.7 trillion by 2032.

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