Analytics Vidhya

NOVEMBER 23, 2021

This article was published as a part of the Data Science Blogathon. Introduction to Classification Algorithms In this article, we shall analyze loan risk using 2 different supervised learning classification algorithms. These algorithms are decision trees and random forests.

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Machine Learning Machine Learning Decision Trees Supervised Learning 399

KDnuggets

JUNE 20, 2022

Also: Decision Tree Algorithm, Explained; 15 Python Coding Interview Questions You Must Know For Data Science; Naïve Bayes Algorithm: Everything You Need to Know; Primary Supervised Learning Algorithms Used in Machine Learning.

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Analytics Vidhya

SEPTEMBER 20, 2021

This article was published as a part of the Data Science Blogathon Introduction In this article, I am going to discuss the math intuition behind the Gradient boosting algorithm. The post Gradient Boosting Algorithm: A Complete Guide for Beginners appeared first on Analytics Vidhya.

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Algorithm Data Science Analytics Analytics 327

Data Science Dojo

SEPTEMBER 5, 2023

Virginia Tech and Microsoft unveil the Algorithm of Thoughts, a breakthrough AI method supercharging idea exploration and reasoning prowess in Large Language Models (LLMs). Notably, CoT at times presents inaccuracies in intermediate steps, a shortcoming AoT aims to rectify by leveraging algorithmic examples for enhanced reliability.

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Analytics Vidhya

MAY 15, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post K-Nearest Neighbour: The Distance-Based Machine Learning Algorithm. Introduction The abbreviation KNN stands for “K-Nearest Neighbour” It is. appeared first on Analytics Vidhya.

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Machine Learning Machine Learning Algorithm Data Science 299

Analytics Vidhya

MAY 20, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction This article aims to explain deep learning and some supervised. The post Introduction to Supervised Deep Learning Algorithms! appeared first on Analytics Vidhya.

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Deep Learning Deep Learning Algorithm Data Science 273

Analytics Vidhya

JUNE 3, 2022

This article was published as a part of the Data Science Blogathon. Introduction Classification problems are often solved using supervised learning algorithms such as Random Forest Classifier, Support Vector Machine, Logistic Regressor (for binary class classification) etc.

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Smart Data Collective

JUNE 4, 2021

What is data science? Data science is analyzing and predicting data, It is an emerging field. Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Data scientists use algorithms for creating data models.

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Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

Data Science Dojo

MAY 27, 2024

A visual representation of generative AI – Source: Analytics Vidhya Generative AI is a growing area in machine learning, involving algorithms that create new content on their own. These algorithms use existing data like text, images, and audio to generate content that looks like it comes from the real world.

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Analytics Vidhya

JUNE 13, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Speech Recognition is a supervised learning task. In the speech. The post MFCC Technique for Speech Recognition appeared first on Analytics Vidhya.

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Supervised Learning Data Science Analytics Analytics 208

Pickl AI

NOVEMBER 4, 2024

Summary: Python for Data Science is crucial for efficiently analysing large datasets. Introduction Python for Data Science has emerged as a pivotal tool in the data-driven world. Key Takeaways Python’s simplicity makes it ideal for Data Analysis. Calculus Learn to understand derivatives and integrals.

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Data Science Python Machine Learning Machine Learning 52

Data Science Dojo

DECEMBER 8, 2023

Zero-shot, one-shot, and few-shot learning are redefining how machines adapt and learn, promising a future where adaptability and generalization reach unprecedented levels. Source: Photo by Hal Gatewood on Unsplash In this exploration, we navigate from the basics of supervised learning to the forefront of adaptive models.

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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. “The

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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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Data Science Dojo

FEBRUARY 15, 2023

Image Credit: Pinterest – Problem solving tools In last week’s post , DS-Dojo introduced our readers to this blog-series’ three focus areas, namely: 1) software development, 2) project-management, and 3) data science. This week, we continue that metaphorical (learning) journey with a fun fact. Better yet, a riddle.

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Data Science Dojo

AUGUST 19, 2024

Industry Adoption: Widespread Implementation: AI and data science are being adopted across various industries, including healthcare, finance, retail, and manufacturing, driving increased demand for skilled professionals. The model learns to map input features to output labels. Privacy: Protecting user privacy and data security.

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Data Science Dojo

MAY 10, 2024

Unsupervised vs. supervised learning for embeddings While vector representation and contextual inference remain important factors in the evolution of LLM embeddings, the lens of comparative analysis also highlights another aspect for discussion. However, labeling data can be an expensive and laborious task.

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IBM Data Science in Practice

MARCH 17, 2025

The broad spectrum of EO data typesincluding radar, LiDAR, hyperspectral, and multispectral imagerypresents unique challenges for image compression techniques. Currently, hand-crafted compression algorithms, often designed for general image data like JPEG2000, are applied.

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

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NYU Center for Data Science

NOVEMBER 15, 2023

Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, *Omar Mahmood (PhD alumnus), Andrew Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi “A Logic for Expressing Log-Precision Transformers” : *William Merrill (PhD student), Ashish Sabharwal “A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks” : Vignesh Kothapalli, Tom (..)

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Pickl AI

APRIL 3, 2023

Accordingly, Machine Learning allows computers to learn and act like humans by providing data. Apparently, ML algorithms ensure to train of the data enabling the new data input to make compelling predictions and deliver accurate results. What is Supervised Learning?

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Data Science Dojo

JUNE 1, 2023

The course covers topics such as supervised learning, unsupervised learning, and reinforcement learning. Machine Learning with Python by Andrew Ng This is an intermediate-level course that teaches you more advanced machine-learning concepts using Python.

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Machine Learning Machine Learning Natural Language Processing Deep Learning 195

Data Science Dojo

MAY 10, 2024

Unsupervised vs. supervised learning for embeddings While vector representation and contextual inference remain important factors in the evolution of LLM embeddings, the lens of comparative analysis also highlights another aspect for discussion. However, labeling data can be an expensive and laborious task.

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Towards AI

APRIL 8, 2024

Supervised Learning First, what exactly is supervised learning? It is the most common type of machine learning that you will use. In supervised machine learning, the machine learning algorithm is trained on a labeled dataset. This is where supervised learning would come in handy.

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Data Science Dojo

DECEMBER 28, 2023

Formatting the data in a way that ML algorithms can understand. Model selection and training: Teaching machines to learn With your data ready, it’s time to select an appropriate ML algorithm. Unsupervised learning algorithms like clustering solve problems without labeled data.

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Machine Learning Machine Learning ML ML 195

Smart Data Collective

JUNE 7, 2019

Machine learning is playing a very important role in improving the functionality of task management applications. In January, Towards Data Science published an article on this very topic. “In Project managers should be aware of the changes that machine learning has brought to task management applications.

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Machine Learning Machine Learning Supervised Learning Support Vector Machines 101

IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

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Becoming Human

MAY 15, 2023

Data Science is a popular as well as vast field; till date, there are a lot of opportunities in this field, and most people, whether they are working professionals or students, everyone want a transition in data science because of its scope. How much to learn? What to do next?

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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.

Machine Learning 105

Machine Learning Machine Learning K-nearest Neighbors Supervised Learning 105

AWS Machine Learning Blog

JANUARY 31, 2025

Increasingly, FMs are completing tasks that were previously solved by supervised learning, which is a subset of machine learning (ML) that involves training algorithms using a labeled dataset. George Lee is AVP, Data Science & Generative AI Lead for International at Travelers Insurance.

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NYU Center for Data Science

JANUARY 25, 2024

In the world of data science, few events garner as much attention and excitement as the annual Neural Information Processing Systems (NeurIPS) conference. 2023’s event, held in New Orleans in December, was no exception, showcasing groundbreaking research from around the globe.

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Computer Science Computer Science Data Science Supervised Learning 94

Data Science Dojo

DECEMBER 8, 2023

Zero-shot, one-shot, and few-shot learning are redefining how machines adapt and learn, promising a future where adaptability and generalization reach unprecedented levels. Source: Photo by Hal Gatewood on Unsplash In this exploration, we navigate from the basics of supervised learning to the forefront of adaptive models.

Supervised Learning 195

Supervised Learning Machine Learning Machine Learning Artificial Intelligence 195

Dataconomy

SEPTEMBER 13, 2023

Data scientists dedicate a significant chunk of their time to data preparation, as revealed by a survey conducted by the data science platform Anaconda. This process involves rectifying or discarding abnormal or non-standard data points and ensuring the accuracy of measurements.

Machine Learning 195

Machine Learning Machine Learning AI AI 195

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? 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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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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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?

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ODSC - Open Data Science

FEBRUARY 10, 2023

Researchers analyzed over 150 terabytes of data which represented the observations of 820 nearby stars. The team found the new algorithm excelled by organizing the data from telescopes into categories. To do this, they first tested the range of algorithms to determine both precision and how often they provided false positives.

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