Dataconomy

MARCH 6, 2025

Algorithms play a crucial role in our everyday lives, often operating behind the scenes to enhance our experiences in the digital world. From the way search engines deliver results to how personal assistants predict our needs, algorithms are the foundational elements that shape modern technology. What is an algorithm?

Algorithm 91

Algorithm Machine Learning Machine Learning Deep Learning 91

ML @ CMU

SEPTEMBER 13, 2024

The answer inherently relates to the definition of memorization for LLMs and the extent to which they memorize their training data. However, even defining memorization for LLMs is challenging, and many existing definitions leave much to be desired. We argue that such a definition provides an intuitive notion of memorization.

Algorithm 327

Algorithm Machine Learning Machine Learning AI 327

Dataconomy

FEBRUARY 18, 2021

Machine learning (ML) is a definite branch of artificial intelligence (AI) that brings together significant insights to solve complex and data-rich business problems by means of algorithms. ML understands the past data that is usually in a raw form to envisage the future outcome. It is gaining more and more.

Machine Learning 254

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 254

KDnuggets

JUNE 12, 2025

But you do need to understand the mathematical concepts behind the algorithms and analyses youll use daily. Part 2: Linear Algebra Every machine learning algorithm youll use relies on linear algebra. Understanding it transforms these algorithms from mysterious black boxes into tools you can use with confidence.

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KDnuggets

SEPTEMBER 12, 2019

It turned out that, if we ask the weak algorithm to create a whole bunch of classifiers (all weak for definition), and then combine them all, what may figure out is a stronger classifier.

Machine Learning 231

Machine Learning Machine Learning Algorithm Python 231

Dataconomy

MARCH 28, 2025

Machine learning algorithms represent a transformative leap in technology, fundamentally changing how data is analyzed and utilized across various industries. What are machine learning algorithms? Outputs: The results generated by the algorithms, whether classifications, predictions, or recommendations based on the patterns identified.

Machine Learning 91

Machine Learning Machine Learning Algorithm K-nearest Neighbors 91

Dataconomy

MAY 16, 2025

Algorithmic transparency is a crucial concept in today’s data-driven world, where algorithms increasingly influence decisions that affect our lives. From search engine results to credit scoring, the algorithms behind these processes often operate behind a veil of secrecy. What is algorithmic transparency?

Algorithm 91

Algorithm AI AI 91

IBM Data Science in Practice

MARCH 13, 2023

In our previous blog, Fairness Explained: Definitions and Metrics , we discuss fairness definitions and fairness metrics through a real-world example. This blog focuses on pre-processing algorithms. Pre-processing algorithms involve modifying the dataset before training the model to remove or reduce the bias present in the data.

Machine Learning 130

Machine Learning Machine Learning Algorithm Data Scientist 130

Analytics Vidhya

AUGUST 6, 2024

Likewise, in mathematics and programming, getting factorial definition of a number requires a unique sequence of multiplication of a series of decrement positive integers. Introduction Suppose for instance that you are cooking a meal that will have a certain taste that you desire if only the sequence of processes is followed as expected.

Python 305

Python Analytics Analytics Algorithm 305

Towards AI

NOVEMBER 11, 2023

Just like looking for a time-efficient path in an unfamiliar route, Greedy Algorithms always select the next step that offers the most obvious and immediate benefit. Greedy Algorithms tend to choose the best option at each step, which gradually gives us a way to achieve the solution in a time-efficient approach.

Algorithm 122

Algorithm Python AI AI 122

Towards AI

FEBRUARY 15, 2024

AI Engineers: Your Definitive Career Roadmap Become a professional certified AI engineer by enrolling in the best AI ML Engineer certifications that help you earn skills to get the highest-paying job. Coding, algorithms, statistics, and big data technologies are especially crucial for AI engineers.

Artificial Intelligence 109

Artificial Intelligence Artificial Intelligence AI AI 109

Analytics Vidhya

DECEMBER 28, 2023

Further in this guide, you will explore temporal graphs in data science—definition, […] The post A Comprehensive Guide to Temporal Graphs in Data Science appeared first on Analytics Vidhya. They capture the temporal dependencies between entities and offer a robust framework for modeling and analyzing time-varying relationships.

Data Science 304

Data Science Analytics Analytics Algorithm 304

Dataconomy

APRIL 28, 2025

Common clustering algorithms Among the various clustering techniques, density-based algorithms are particularly effective in revealing clusters within data. HDBSCAN (Self-Adjusting Clustering): This advanced algorithm adapts to varying cluster densities, offering flexibility with reduced human oversight.

Clustering 91

Clustering Data Analysis Data Analysis Algorithm 91

Dataconomy

APRIL 24, 2025

ML Interpretability is a crucial aspect of machine learning that enables practitioners and stakeholders to trust the outputs of complex algorithms. Unlike explainability, which aims to articulate the internal workings of an algorithm, interpretability concentrates on recognizing the significant features affecting model behavior.

ML 91

ML ML Algorithm Machine Learning 91

Dataconomy

APRIL 28, 2025

The rise of artificial intelligence and machine learning has allowed for the development of recommendation algorithms and personalized content delivery systems. In the realm of machine learning, this idea is implemented through sophisticated algorithms that can incorporate new contextual data.

Natural Language Processing 91

Natural Language Processing Machine Learning Machine Learning Algorithm 91

PyImageSearch

DECEMBER 23, 2024

These scenarios demand efficient algorithms to process and retrieve relevant data swiftly. This is where Approximate Nearest Neighbor (ANN) search algorithms come into play. ANN algorithms are designed to quickly find data points close to a given query point without necessarily being the absolute closest.

K-nearest Neighbors 118

K-nearest Neighbors Algorithm Deep Learning Deep Learning 118

Dataconomy

MARCH 11, 2025

The concept of a target function is an essential building block in the realm of machine learning, influencing how algorithms interpret data and make predictions. It is the mechanism that algorithms strive to approximate as they learn from provided data. Input (I): The data fed into the algorithm for analysis.

Machine Learning 91

Machine Learning Machine Learning Deep Learning Deep Learning 91

Dataconomy

MARCH 25, 2025

Definition of decision boundary The definition of a decision boundary is rooted in its functionality within classification algorithms. It can manifest in various forms, such as linear or non-linear, depending on the underlying data distribution and the algorithm employed.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Clustering 91

Dataconomy

APRIL 29, 2025

Definition of model fairness Model fairness is concerned with preventing AI predictions from reinforcing existing biases. Influences stemming from algorithmic choices: The design and implementation of algorithms can inadvertently introduce bias by prioritizing certain attributes over others.

Machine Learning 103

Machine Learning Machine Learning AI AI 103

Dataconomy

APRIL 4, 2025

Definition and importance Convex optimization revolves around functions and constraints that exhibit specific properties. Definition of convex functions A function ( f(x) ) is convex if, for any two points ( x_1 ) and ( x_2 ), the following condition holds: [ f(tx_1 + (1-t)x_2) leq tf(x_1) + (1-t)f(x_2) text{ for all } t in [0, 1].

Machine Learning 91

Machine Learning Machine Learning Support Vector Machines Algorithm 91

Towards AI

NOVEMBER 16, 2024

Keswani’s Algorithm introduces a novel approach to solving two-player non-convex min-max optimization problems, particularly in differentiable sequential games where the sequence of player actions is crucial. Keswani’s Algorithm: The algorithm essentially makes response function : maxy∈{R^m} f (.,

Algorithm 103

Algorithm ML ML AI 103

Dataconomy

APRIL 21, 2025

They influence the choice of algorithms and the structure of models. This includes converting categorical data into numerical values, which is often necessary for algorithms to work effectively. Definition and types of categorical data Categorical data can be classified into two primary types: nominal and ordinal.

Machine Learning 91

Machine Learning Machine Learning Algorithm Decision Trees 91

Dataconomy

APRIL 29, 2025

This property not only shapes our statistical methods, but it also influences how algorithms learn from data, making IID a key theme in data science. Definition and explanation of IID The term “IID” encapsulates two core principles: independence and identical distribution.

Machine Learning 91

Machine Learning Machine Learning Algorithm Data Science 91

DrivenData Labs

MAY 12, 2025

After the challenge, the research team at NOAA and NCEI worked with one of the winners to implement an ensemble of the top two models, incorporating into NOAA's High Definition Geomagnetic Model (HDGM) and making the predictions publicly available in real-time. A sample frame is shown with the most likely species identified.

Algorithm 130

Algorithm Machine Learning Machine Learning Deep Learning 130

Dataconomy

MAY 20, 2025

These two techniques, while related, have distinct definitions and applications. Definition of extrapolation Extrapolation involves estimating unknown values that lie outside the range of your known data points. Decision trees: Estimation methods help build these algorithms, enhancing their predictive power.

Predictive Analytics 91

Predictive Analytics Decision Trees Data Analysis Data Analysis 91

Data Science Dojo

APRIL 20, 2023

However, with the rise of artificial intelligence, the definition of creativity is changing. In this article, we will discuss the impact of AI on art, including the definition of AI-generated art like Midjourney, the controversy surrounding its validity as “real” art, and its potential to revolutionize the art world.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

Understanding up front which preprocessing techniques and algorithm types provide best results reduces the time to develop, train, and deploy the right model. An AutoML tool applies a combination of different algorithms and various preprocessing techniques to your data. The following screenshot shows the top rows of the dataset.

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Algorithm AWS ML ML 126

PyImageSearch

APRIL 7, 2025

Mathematical Definition In an matrix, can be diagonalized and expressed in the following form: where: is an orthogonal matrix (i.e., ) is an diagonal matrix whose diagonal elements are non-negative real numbers (known as singular values). Figure 6: Image compression using the SVD algorithm (source: ScienceDirect ).

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Algorithm Deep Learning Deep Learning Python 108

Dataconomy

MARCH 10, 2025

Understanding its role can enhance the effectiveness of machine learning algorithms, ensuring they make accurate predictions and decisions based on real-world data. Ground truth in machine learning refers to the precise, labeled data that provides a benchmark for various algorithms. What is ground truth in machine learning?

Machine Learning 91

Machine Learning Machine Learning Algorithm Cross Validation 91

Dataconomy

MARCH 12, 2025

Understanding this concept is essential, as it helps practitioners evaluate the effectiveness of complex algorithms by comparing them to simpler baseline models. It provides insights into the expected performance of machine learning algorithms and sets the stage for determining the success of more advanced modeling techniques.

Machine Learning 91

Machine Learning Machine Learning Algorithm ML 91

Dataconomy

MARCH 21, 2025

Definition and significance of NLP Natural Language Processing is a subset of AI that combines computational linguistics and advanced algorithms to facilitate human-computer interaction. Algorithm development The choice between rule-based and machine learning algorithms is crucial in NLP.

Natural Language Processing 103

Natural Language Processing Deep Learning Deep Learning Machine Learning 103

Hacker News

MAY 24, 2024

We present a new hybrid digital-analog algorithm for training neural networks that is equivalent to NGD in a certain parameter regime but avoids prohibitively costly linear system solves. Our algorithm exploits the thermodynamic properties of an analog system at equilibrium, and hence requires an analog thermodynamic computer.

Algorithm 139

Algorithm 139

Flipboard

APRIL 26, 2025

Despite its many guardrails , ChatGPT is still able to generate controversial imagery depending on your definition of "controversial,"that is. After twice affirming that we wanted to go ahead, ChatGPT finally spat out an image it titled, with aplomb, "The Algorithm Decides."

Algorithm 154

Algorithm AI AI 154

Dataconomy

APRIL 4, 2025

Definition of decision trees A decision tree is a graphical representation of possible solutions to a problem based on certain conditions. Learning process in decision trees The learning process in decision trees relies on recursive partitioning, where the algorithm repeatedly divides the dataset into smaller and more homogeneous subsets.

Decision Trees 91

Decision Trees Machine Learning Machine Learning Algorithm 91

Dataconomy

MARCH 25, 2025

RMSProp is an essential optimization algorithm that has gained prominence in the fields of deep learning and machine learning. Core principles of RMSProp RMSProp is an advanced optimization algorithm that modifies gradient descent to better address challenging aspects of training.

Deep Learning 91

Deep Learning Deep Learning Algorithm Machine Learning 91

Dataconomy

APRIL 21, 2025

Definition of classification threshold A classification threshold is a specific value used as a cutoff point, where predicted probabilities generated by a model are transformed into discrete class labels. Development of customized algorithms aimed at specific use cases.

Machine Learning 91

Machine Learning Machine Learning Algorithm 91

Dataconomy

MARCH 25, 2025

Their role extends beyond mere classification; they also facilitate regression and clustering, demonstrating their versatility across various algorithms. Definition of hyperplane A hyperplane can be defined as a flat affine subspace that is one dimension lower than the ambient space in which it exists. What is a hyperplane?

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Clustering 91