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.

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Towards AI

APRIL 24, 2025

Last Updated on April 24, 2025 by Editorial Team Author(s): SETIA BUDI SUMANDRA Originally published on Towards AI. Thats the motto of Unsupervised Learning a fascinating branch of machine learning where algorithms learn patterns from unlabeled data. Join thousands of data leaders on the AI newsletter. No worries!

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Pickl AI

APRIL 3, 2023

Therefore, Supervised Learning vs Unsupervised Learning is part of Machine Learning. Let’s learn more about supervised and Unsupervised Learning and evaluate their differences. What is Supervised Learning? What is Unsupervised Learning?

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Pickl AI

JANUARY 21, 2025

Types of Machine Learning Algorithms Machine Learning has become an integral part of modern technology, enabling systems to learn from data and improve over time without explicit programming. The goal is to learn a mapping from inputs to outputs, allowing the model to make predictions on unseen data.

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Data Science Dojo

MAY 10, 2024

Their impact on ML tasks has made them a cornerstone of AI advancements. Read on to understand the role of embeddings in generative AI Let’s take a step back and travel through the journey of LLM embeddings from the start to the present day, understanding their evolution every step of the way.

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Towards AI

JANUARY 11, 2024

Last Updated on January 12, 2024 by Editorial Team Author(s): Davide Nardini Originally published on Towards AI. Arguably, one of the most important concepts in machine learning is classification. This article will illustrate the difference between classification and regression in machine learning. Published via Towards AI

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Towards AI

APRIL 8, 2024

Last Updated on April 8, 2024 by Editorial Team Author(s): Eashan Mahajan Originally published on Towards AI. Photo by Arseny Togulev on Unsplash With machine learning’s surge of popularity in the past few years, more and more people spend hours each day trying to learn as much as they can. Let’s get right into it.

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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.

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AWS Machine Learning Blog

FEBRUARY 13, 2025

Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case. We can then use pgvector to find articles that are clustered together.

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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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Pickl AI

MARCH 13, 2023

INTRODUCTION Machine Learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that allow computers to learn and make predictions or decisions based on data, without being explicitly programmed. WHAT IS CLUSTERING? Those groups are referred to as clusters.

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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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Pickl AI

FEBRUARY 17, 2025

This scenario highlights a common reality in the Machine Learning landscape: despite the hype surrounding ML capabilities, many projects fail to deliver expected results due to various challenges. Statistics reveal that 81% of companies struggle with AI-related issues ranging from technical obstacles to economic concerns.

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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., Taxonomy of the self-supervised learning Wang et al. 2022’s paper.

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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.

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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.

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Dataconomy

AUGUST 31, 2023

Machine learning models have already started to take up a lot of space in our lives, even if we are not consciously aware of it. Embracing AI systems and technology day by day, humanity is experiencing perhaps the fastest development in recent years. You want an example: ChatGPT, Alexa, autonomous vehicles and many more on the way.

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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.

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Towards AI

APRIL 18, 2023

Last Updated on April 21, 2023 by Editorial Team Author(s): Sriram Parthasarathy Originally published on Towards AI. Building disruptive Computer Vision applications with No Fine-Tuning Imagine a world where computer vision models could learn from any set of images without relying on labels or fine-tuning. Sounds futuristic, right?

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Towards AI

JULY 22, 2023

Last Updated on July 24, 2023 by Editorial Team Author(s): Cristian Originally published on Towards AI. In the context of Machine Learning, data can be anything from images, text, numbers, to anything else that the computer can process and learn from. Instead, it learns by finding patterns and structures in the input data.

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NYU Center for Data Science

JANUARY 25, 2024

Rudner (Instructor), Yann LeCun (Professor of Computer Science, Neural Science, Data Science, and Electrical and Computer Engineering) “ Reverse Engineering Self-Supervised Learning ” by Ido Ben-Shaul, Ravid Shwartz-Ziv (Faculty Fellow), Tomer Galanti, Shai Dekel, Yann LeCun (Professor of Computer Science, Neural Science, Data Science, and Electrical (..)

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ODSC - Open Data Science

APRIL 24, 2023

Botnet Detection at Scale — Lessons Learned From Clustering Billions of Web Attacks Into Botnets Editor’s note: Ori Nakar is a speaker for ODSC Europe this June. Be sure to check out his talk, “ Botnet detection at scale — Lesson learned from clustering billions of web attacks into botnets ,” there!

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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. We continued our efforts in developing new algorithms for handling large datasets in various areas, including unsupervised and semi-supervised learning , graph-based learning , clustering , and large-scale optimization.

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Towards AI

MARCH 11, 2025

Author(s): Arthur Kakande Originally published on Towards AI. Photo by Hyundai Motor Group on Unsplash When we learn from labeled data, we call it supervised learning. When we learn by grouping similar items, we call it clustering.

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Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

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Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

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K-nearest Neighbors Decision Trees AI AI 91

Pickl AI

JULY 17, 2023

Machine Learning is a subset of artificial intelligence (AI) that focuses on developing models and algorithms that train the machine to think and work like a human. Unsupervised Learning Algorithms Unsupervised Learning Algorithms tend to perform more complex processing tasks in comparison to supervised learning.

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IBM Journey to AI blog

SEPTEMBER 20, 2023

Foundational models (FMs) are marking the beginning of a new era in machine learning (ML) and artificial intelligence (AI) , which is leading to faster development of AI that can be adapted to a wide range of downstream tasks and fine-tuned for an array of applications. What are large language models?

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Towards AI

APRIL 10, 2024

Last Updated on April 11, 2024 by Editorial Team Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. A non-parametric, supervised learning classifier, the K-Nearest Neighbors (k-NN) algorithm uses proximity to classify or predict how a single data point will be grouped. What is K Nearest Neighbor?

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Pickl AI

NOVEMBER 13, 2024

In this blog, we will explore the four primary types of Machine Learning: Supervised Learning, UnSupervised Learning, semi-Supervised Learning, and Reinforcement Learning. Understanding these types is crucial for anyone looking to harness the power of Machine Learning in their projects or career.

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Towards AI

FEBRUARY 20, 2024

Last Updated on February 20, 2024 by Editorial Team Author(s): Vaishnavi Seetharama Originally published on Towards AI. Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms.

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How to Learn Machine Learning

MAY 2, 2025

Welcome to this comprehensive guide on Azure Machine Learning , Microsoft’s powerful cloud-based platform that’s revolutionizing how organizations build, deploy, and manage machine learning models. This is where Azure Machine Learning shines by democratizing access to advanced AI capabilities. Awesome, right?

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IBM Journey to AI blog

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. Machine learning is a subset of AI. Deep learning is a subfield of machine learning, and neural networks make up the backbone of deep learning algorithms.

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Mlearning.ai

FEBRUARY 17, 2023

Basically, Machine learning is a part of the Artificial intelligence field, which is mainly defined as a technic that gives the possibility to predict the future based on a massive amount of past known or unknown data. ML algorithms can be broadly divided into supervised learning , unsupervised learning , and reinforcement learning.

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Flipboard

DECEMBER 6, 2023

The model then uses a clustering algorithm to group the sentences into clusters. The sentences that are closest to the center of each cluster are selected to form the summary. In addition, he builds and deploys AI/ML models on the AWS Cloud. These models are larger in parameter size and perform better in tasks.

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Pickl AI

JANUARY 2, 2025

Summary: Entropy in Machine Learning quantifies uncertainty, driving better decision-making in algorithms. It optimises decision trees, probabilistic models, clustering, and reinforcement learning. Entropy enhances clustering, federated learning, finance, and bioinformatics.

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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.

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