NYU Center for Data Science

JULY 5, 2024

Our study demonstrates that machine supervision significantly improves two crucial medical imaging tasks: classification and segmentation,” said Cirrone, who leads AI efforts at the Colton Center for Autoimmunity at NYU Langone.

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Dataconomy

MAY 29, 2023

In the field of AI and ML, QR codes are incredibly helpful for improving predictive analytics and gaining insightful knowledge from massive data sets. These algorithms allow AI systems to recognize patterns, forecast outcomes, and adjust to new situations.

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Towards AI

SEPTEMBER 7, 2023

Last Updated on September 8, 2023 by Editorial Team Author(s): Louis Bouchard Originally published on Towards AI. An analogy to explain how deep learning works… This member-only story is on us. link] When we talk about artificial intelligence, or AI, we tend to mean deep learning. Published via Towards AI

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Data Science Dojo

JULY 2, 2024

Adaptive AI has risen as a transformational technological concept over the years, leading Gartner to name it as a top strategic tech trend for 2023. It is a step ahead within the realm of artificial intelligence (AI). As the use of AI has expanded into various arenas of the world, the technology has also developed over time.

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IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. Machine learning is a subset of AI. What is artificial intelligence (AI)?

Deep Learning 71

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NYU Center for Data Science

SEPTEMBER 13, 2024

The world of multi-view self-supervised learning (SSL) can be loosely grouped into four families of methods: contrastive learning, clustering, distillation/momentum, and redundancy reduction. This behavior appears to contradict the classical bias-variance tradeoff, which traditionally suggests a U-shaped error curve.

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Data Science Dojo

JUNE 1, 2023

Machine learning courses Top free machine learning courses Here are 9 free machine learning courses from top universities that you can take online to upgrade your skills: 1. The course covers topics such as supervised learning, unsupervised learning, and reinforcement learning.

Machine Learning 195

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Pickl AI

AUGUST 1, 2024

Summary : Deep Learning engineers specialise in designing, developing, and implementing neural networks to solve complex problems. Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 7, 2025

Summary: Machine Learning and Deep Learning are AI subsets with distinct applications. Understanding their differences helps choose the right approach for AI-driven innovations across various industries. Choose ML for structured data and interpretability; use DL for large-scale automation and deep insights.

Deep Learning 52

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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 Deep learning notoriously needs a lot of data in training.

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Dataconomy

APRIL 18, 2023

With the rise of AI-generated art and AI-powered chatbots like ChatGPT, it’s clear that artificial intelligence has become a ubiquitous part of our daily lives. These cutting-edge technologies have captured the public imagination, fueling speculation about the future of AI and its impact on society.

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Towards AI

APRIL 7, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. You just want to create and analyze simple maps not to learn algebra all over again. This function can be improved by AI and ML, which allow GIS to produce insights, automate procedures, and learn from data. Types of Machine Learning for GIS 1.

Machine Learning 105

Machine Learning Machine Learning K-nearest Neighbors Supervised Learning 105

Dataconomy

MAY 25, 2023

By harnessing the power of AI in IoT, we can create intelligent ecosystems where devices seamlessly communicate, collaborate, and make intelligent choices to improve our lives. Let’s explore the fascinating intersection of these two technologies and understand how AI enhances the functionalities of IoT.

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Becoming Human

MARCH 16, 2023

AI drug discovery is exploding. Overhyped or not, investments in AI drug discovery jumped from $450 million in 2014 to a whopping $58 billion in 2021. AI has already helped identify promising candidate therapeutics, and it didn’t take years but months or even days. We will look at success stories, AI benefits, and limitations.

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Flipboard

MARCH 13, 2023

Yes, large language models (LLMs) hallucinate , a concept popularized by Google AI researchers in 2018. That feedback is used to adjust the reward predictor neural network, and the updated reward predictor neural network is used to adjust the behavior of the AI model. Most of what we learn has nothing to do with language.” “We

Deep Learning 172

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Smart Data Collective

JUNE 4, 2021

Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Learning the various categories of machine learning, associated algorithms, and their performance parameters is the first step of machine learning. In supervised learning, a variable is predicted.

Data Science 133

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Towards AI

AUGUST 29, 2023

Last Updated on August 30, 2023 by Editorial Team Author(s): Tan Pengshi Alvin Originally published on Towards AI. Introducing the backbone of Reinforcement Learning — The Markov Decision Process This member-only story is on us. Join thousands of data leaders on the AI newsletter. Published via Towards AI

Supervised Learning 105

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Heartbeat

OCTOBER 11, 2023

This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. Supervised, unsupervised, and reinforcement learning : Machine learning can be categorized into different types based on the learning approach.

Deep Learning 52

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Dataconomy

OCTOBER 5, 2023

If you are interested in technology at all, it is hard not to be fascinated by AI technologies. Whether it’s pushing the limits of creativity with its generative abilities or knowing our needs better than us with its advanced analysis capabilities, many sectors have already taken a slice of the huge AI pie.

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Data Science Blog

MARCH 14, 2023

Von Big Data über Data Science zu AI Einer der Gründe, warum Big Data insbesondere nach der Euphorie wieder aus der Diskussion verschwand, war der Leitspruch “S**t in, s**t out” und die Kernaussage, dass Daten in großen Mengen nicht viel wert seien, wenn die Datenqualität nicht stimme. Artificial Intelligence (AI) ersetzt.

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AssemblyAI

MAY 17, 2023

Generative AI has made great strides in the language domain. GPT-4’s performance on various example compared to GPT-3.5 ( source ) These Generative AI models are progressively migrating from the ivory tower and finding themselves integrated into our everyday lives through tools like Microsoft’s Copilot.

Supervised Learning 119

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Pickl AI

SEPTEMBER 16, 2024

Summary : Deep Belief Networks (DBNs) are Deep Learning models that use Restricted Boltzmann Machines and feedforward networks to learn hierarchical features and model complex data distributions. What is a Deep Belief Network (DBN)? They are effective in image recognition, NLP, and speech recognition.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Supervised Learning 52

IBM Journey to AI blog

MAY 9, 2023

We stand on the frontier of an AI revolution. Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. It sounds like a joke, but it’s not, as anyone who has tried to solve business problems with AI may know.

AI 139

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Dataconomy

MAY 4, 2023

Machine learning applications in healthcare are revolutionizing the way we approach disease prevention and treatment Machine learning is broadly classified into three categories: supervised learning, unsupervised learning, and reinforcement learning.

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Mlearning.ai

DECEMBER 13, 2023

Mastering Deep Learning and AI Interview Questions: What You Need to Know Image created by the author on Canva Knowledge is power, but enthusiasm pulls the switch.” Ever wondered what it takes to excel in deep learning interviews? Explain how you would implement transfer learning in a deep learning model.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Data Science 52

Pickl AI

NOVEMBER 28, 2024

Summary: Generative Adversarial Network (GANs) in Deep Learning generate realistic synthetic data through a competitive framework between two networks: the Generator and the Discriminator. In answering the question, “What is a Generative Adversarial Network (GAN) in Deep Learning?”

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IBM Journey to AI blog

DECEMBER 20, 2023

That’s why diversifying enterprise AI and ML usage can prove invaluable to maintaining a competitive edge. What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

Mlearning.ai

JULY 11, 2023

Deep learning has transformed artificial intelligence, allowing machines to learn and make smart decisions. If you’re interested in exploring deep learning, this step-by-step guide will help you learn the basics and develop the necessary skills. Also, learn about common algorithms used in machine learning.

Deep Learning 40

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NYU Center for Data Science

MAY 31, 2023

CDS Assistant Professor/Faculty Fellow Jacopo Cirrone works at the intersection of machine learning and healthcare, recently publishing two papers that expand deep learning research within these fields. To learn more about data science’s future in medical imaging and healthcare, CDS spoke with Jacopo.

Machine Learning 74

Machine Learning Machine Learning Deep Learning Deep Learning 74

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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Explosion

APRIL 1, 2017

Prodigy features many of the ideas and solutions for data collection and supervised learning outlined in this blog post. It’s a cloud-free, downloadable tool and comes with powerful active learning models. This post is based on a talk I gave at “How AI Will Shape the Future of Work” at Founders in Copenhagen in January.

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Dataconomy

MAY 22, 2023

There are various types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. In supervised learning, the model learns from labeled examples, where the input data is paired with corresponding target labels.

ML 233

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Hacker News

MARCH 25, 2022

If you want to ride the next big wave in AI, grab a transformer. A transformer model is a neural network that learns context and thus meaning by tracking relationships in sequential data like the words in this sentence. They’re driving a wave of advances in machine learning some have dubbed transformer AI.

Machine Learning 182

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IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Hacker News

MAY 3, 2023

In the grand tapestry of modern artificial intelligence, how do we ensure that the threads we weave when designing powerful AI systems align with the intricate patterns of human values? This question lies at the heart of AI alignment , a field that seeks to harmonize the actions of AI systems with our own goals and interests.

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Data Science Dojo

SEPTEMBER 11, 2023

The developers have taken a proactive stance to ensure responsible AI practices are embedded in PaLM 2’s functionality. Real-World Applications and Use Cases of PaLM 2: The features and capabilities of PaLM 2’s model extends to a myriad of real-world applications, revolutionizing and changing the way we interact with technology.

Natural Language Processing 195

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IBM Journey to AI blog

JUNE 14, 2023

Sometimes the problem with artificial intelligence (AI) and automation is that they are too labor intensive. Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. This is an open, hard problem for the entire field of AI applications.

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