NYU Center for Data Science

NOVEMBER 3, 2023

Self-supervised learning (SSL) has emerged as a powerful technique for training deep neural networks without extensive labeled data. Rudner, among others, and “ To Compress or Not to Compress — Self-Supervised Learning and Information Theory: A Review.” This is how humans learn.”

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Dataconomy

APRIL 17, 2025

Image-to-image translation is a fascinating area of generative AI that harnesses advanced algorithms to transform existing images into new forms while retaining essential characteristics. Understanding generative AI Generative AI encompasses a range of algorithms designed to create new content based on pre-existing data.

Deep Learning 91

Deep Learning Deep Learning Supervised Learning Algorithm 91

Flipboard

JUNE 13, 2025

Yet, navigating the world of AI can feel overwhelming, with its complex algorithms, vast datasets, and ever-evolving tools. Essential AI Skills Guide TL;DR Key Takeaways : Proficiency in programming languages like Python, R, and Java is essential for AI development, allowing efficient coding and implementation of algorithms.

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Artificial Intelligence Artificial Intelligence Exploratory Data Analysis Machine Learning 73

Dataconomy

MARCH 5, 2025

is dedicated to creating systems that can learn and adapt, a fundamental step toward achieving General-Purpose Artificial Intelligence (AGI). Technology and methodology DeepMind’s approach revolves around sophisticated machine learning methods that enable AI to interact with its environment and learn from experience.

Deep Learning 91

Deep Learning Deep Learning Artificial Intelligence Artificial Intelligence 91

Dataconomy

APRIL 29, 2025

Binary classification is a supervised learning method designed to categorize data into one of two possible outcomes. Overview of classification in machine learning Classification serves as a foundational method in machine learning, where algorithms are trained on labeled datasets to make predictions.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Algorithm 91

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. I don’t think it will replace existing algorithms,” Shwartz-Ziv noted.

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How to Learn Machine Learning

MAY 7, 2025

In the world of AI, you might hear a lot of Machine Learning vs Deep Learning. Introduction to Deep Learning vs Machine Learning To a lot of people, the terms Deep Learning and Machine Learning seem like buzzwords in the AI world. What is Deep Learning?

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Data Science Dojo

JUNE 1, 2023

Machine Learning for Absolute Beginners by Kirill Eremenko and Hadelin de Ponteves This is another beginner-level course that teaches you the basics of machine learning using Python. The course covers topics such as supervised learning, unsupervised learning, and reinforcement learning.

Machine Learning 195

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BAIR

JULY 9, 2023

Figure 1: stepwise behavior in self-supervised learning. When training common SSL algorithms, we find that the loss descends in a stepwise fashion (top left) and the learned embeddings iteratively increase in dimensionality (bottom left). Our work finds the analogous results for SSL.

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Dataconomy

FEBRUARY 26, 2025

Here are notable examples: Facial recognition software Facial recognition algorithms analyze facial features to identify individuals. Relation of pattern recognition to AI and machine learning Pattern recognition is a vital subset of machine learning and AI.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Decision Trees 91

Google Research AI blog

FEBRUARY 10, 2023

Robust algorithm design is the backbone of systems across Google, particularly for our ML and AI models. Hence, developing algorithms with improved efficiency, performance and speed remains a high priority as it empowers services ranging from Search and Ads to Maps and YouTube. You can find other posts in the series here.)

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Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. Whereas in machine learning, the algorithm understands the data and creates the logic. Learning the various categories of machine learning, associated algorithms, and their performance parameters is the first step of machine learning.

Data Science 133

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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. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other? Machine learning is a subset of AI.

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Deep Learning Deep Learning Machine Learning Machine Learning 71

Data Science Dojo

JULY 2, 2024

It is a form of AI that learns, adapts, and improves as it encounters changes, both in data and the environment. Unlike traditional AI, which follows set rules and algorithms and tends to fall apart when faced with obstacles, adaptive AI systems can modify their behavior based on their experiences. What is Adaptive AI?

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Machine Learning Mastery

DECEMBER 31, 2022

Last Updated on January 1, 2023 While a logistic regression classifier is used for binary class classification, softmax classifier is a supervised learning algorithm which is mostly used when multiple classes are involved. Softmax classifier works by assigning a probability distribution to each class.

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Dataconomy

MAY 22, 2023

By dividing the workload and data across multiple nodes, distributed learning enables parallel processing, leading to faster and more efficient training of machine learning models. There are various types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning.

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Dataconomy

MAY 29, 2023

These algorithms allow AI systems to recognize patterns, forecast outcomes, and adjust to new situations. The applications of AI span diverse domains, including natural language processing, computer vision, robotics, expert systems, and machine learning. QR codes also contribute to access control and security within AI and ML systems.

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Pickl AI

FEBRUARY 7, 2025

Summary: Machine Learning and Deep Learning are AI subsets with distinct applications. Introduction In todays world of AI, both Machine Learning (ML) and Deep Learning (DL) are transforming industries, yet many confuse the two. The model learns from the input-output pairs and predicts outcomes for new data.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

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

Dataconomy

MAY 4, 2023

From predicting disease outbreaks to identifying complex medical patterns and helping researchers develop targeted therapies, the potential applications of machine learning in healthcare are vast and varied. What is machine learning? From personalized medicine to disease prevention, the possibilities are endless.

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Towards AI

APRIL 7, 2024

Created by the author with DALL E-3 Statistics, regression model, algorithm validation, Random Forest, K Nearest Neighbors and Naïve Bayes— what in God’s name do all these complicated concepts have to do with you as a simple GIS analyst? You just want to create and analyze simple maps not to learn algebra all over again.

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Machine Learning Machine Learning K-nearest Neighbors Supervised Learning 102

Heartbeat

OCTOBER 11, 2023

A key component of artificial intelligence is training algorithms to make predictions or judgments based on data. 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. What is Machine Learning?

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Deep Learning Deep Learning Machine Learning Machine Learning 52

Dataconomy

APRIL 18, 2023

Additionally, it is crucial to comprehend the fundamental concepts that underlie AI, including neural networks, algorithms, and data structures. AI systems use a combination of algorithms, machine learning techniques, and data analytics to simulate human intelligence. What is artificial intelligence?

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IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

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.

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Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans. By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions.

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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

Pickl AI

APRIL 13, 2025

Summary: Classifier in Machine Learning involves categorizing data into predefined classes using algorithms like Logistic Regression and Decision Trees. Introduction Machine Learning has revolutionized how we process and analyse data, enabling systems to learn patterns and make predictions.

Machine Learning 52

Machine Learning Machine Learning Decision Trees K-nearest Neighbors 52

ML @ CMU

APRIL 23, 2025

The paper analyzes two families of self-improvement algorithms: one based on supervised fine-tuning (SFT) and one on reinforcement learning (RLHF). The authors combine learned diffusion models with classical planning algorithms to generate realistic, safe multi-robot trajectories.

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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

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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.

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Dataconomy

OCTOBER 5, 2023

AI practitioners choose an appropriate machine learning model or algorithm that aligns with the problem at hand. Common choices include neural networks (used in deep learning), decision trees, support vector machines, and more. Another form of machine learning algorithm is known as unsupervised learning.

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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. Finally, we will look at some of the recent semi-supervised medical image segmentation algorithms.

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Algorithm 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?”

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

AUGUST 28, 2024

Summary: This comprehensive guide covers the basics of classification algorithms, key techniques like Logistic Regression and SVM, and advanced topics such as handling imbalanced datasets. It also includes practical implementation steps and discusses the future of classification in Machine Learning. What is Classification?

Machine Learning 52

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Data Science Dojo

SEPTEMBER 11, 2023

These complex algorithms are the backbone upon which our modern technological advancements rest and which are doing wonders for natural language communication. PaLM 2 stands for “ Progressive and Adaptive Language Model 2 ” and Llama 2 is short for “ Language Learning and Mastery Algorithm 2 ”.

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Pickl AI

OCTOBER 9, 2023

However, with the emergence of Machine Learning algorithms, the retail industry has seen a revolutionary shift in demand forecasting capabilities. This technology allows computers to learn from historical data, identify patterns, and make data-driven decisions without explicit programming.

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