Dataconomy

APRIL 16, 2025

This technique plays a crucial role in various applications, from image recognition to financial forecasting, showcasing its significance in the era of artificial intelligence. Supervised learning refers to a subset of machine learning techniques where algorithms learn from labeled datasets. What is supervised learning?

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PyImageSearch

SEPTEMBER 16, 2024

Home Table of Contents Credit Card Fraud Detection Using Spectral Clustering Understanding Anomaly Detection: Concepts, Types and Algorithms What Is Anomaly Detection? Spectral clustering, a technique rooted in graph theory, offers a unique way to detect anomalies by transforming data into a graph and analyzing its spectral properties.

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Pickl AI

APRIL 9, 2025

Summary: Artificial Intelligence (AI) and Deep Learning (DL) are often confused. AI vs Deep Learning is a common topic of discussion, as AI encompasses broader intelligent systems, while DL is a subset focused on neural networks. Both Drive Technological Innovation: Transform industries with intelligent systems.

Deep Learning 52

Deep Learning Deep Learning Artificial Intelligence Artificial Intelligence 52

Pickl AI

SEPTEMBER 23, 2024

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. Introduction Artificial Intelligence (AI) and Data Science are revolutionising how we analyse data, make decisions, and solve complex problems.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

IBM Journey to AI blog

DECEMBER 20, 2023

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. Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others.

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AWS Machine Learning Blog

JANUARY 17, 2024

We can analyze activities by identifying stops made by the user or mobile device by clustering pings using ML models in Amazon SageMaker. A cluster of pings represents popular spots where devices gathered or stopped, such as stores or restaurants. Manually managing a DIY compute cluster is slow and expensive.

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Mlearning.ai

FEBRUARY 17, 2023

A complete explanation of the most widely practical and efficient field, that nowadays has an impact on every industry Photo by Thomas T on Unsplash Machine learning has become one of the most rapidly evolving and popular fields of technology in recent years. Clustering is similar to classification, but the basis is different.

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How to Learn Machine Learning

MARCH 25, 2025

Some common supervised learning algorithms include decision trees, random forests, support vector machines, and linear regression. Clustering algorithms like k-means, hierarchical clustering, and density-based clustering are widely used. Unsupervised learning outputs are not as direct.

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Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. An AI model is a crucial part of artificial intelligence. What is an AI model?

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Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. An AI model is a crucial part of artificial intelligence. What is an AI model?

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K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

JUNE 13, 2023

Decision intelligence is an innovative approach that blends the realms of data analysis, artificial intelligence, and human judgment to empower businesses with actionable insights. Think of decision intelligence as a synergy between the human mind and cutting-edge algorithms. What is decision intelligence?

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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

AWS Machine Learning Blog

FEBRUARY 25, 2025

SVM-based classifier: Amazon Titan Embeddings In this scenario, it is likely that user interactions belonging to the three main categories ( Conversation , Services , and Document_Translation ) form distinct clusters or groups within the embedding space. This doesnt imply that clusters coudnt be highly separable in higher dimensions.

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Mlearning.ai

APRIL 8, 2023

What is Natural Language Processing (NLP) Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that deals with interactions between computers and human languages. The earlier models that were SOTA for NLP mainly fell under the traditional machine learning algorithms.

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Dataconomy

AUGUST 9, 2023

But as in every aspect of our lives, Machine Learning algorithms and artificial intelligence help us in network traffic analysis. How could machine learning be used in network traffic analysis? Some common algorithms include: Random Forest : This ensemble learning algorithm is effective for classification tasks.

Machine Learning 91

Machine Learning Machine Learning ML ML 91

Pickl AI

FEBRUARY 7, 2025

Introduction In todays world of AI, both Machine Learning (ML) and Deep Learning (DL) are transforming industries, yet many confuse the two. While both are subsets of Artificial Intelligence, they differ significantly regarding techniques and applications. What is Machine Learning?

Deep Learning 52

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Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. Future Trends Exploring emerging trends in Big Data, such as the rise of edge computing, quantum computing, and advancements in artificial intelligence.

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Heartbeat

OCTOBER 25, 2023

The development of explainable and interpretable machine learning models will enhance the trustworthiness of predictions and enable researchers to gain deeper insights into the underlying biological mechanisms. Clustering algorithms can group similar biological samples or identify distinct subtypes within a disease.

Machine Learning 52

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Pickl AI

SEPTEMBER 12, 2024

Artificial Intelligence (AI): A branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. Association Rule Learning: A rule-based Machine Learning method to discover interesting relationships between variables in large databases.

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How to Learn Machine Learning

AUGUST 14, 2024

scikit-learn – The most widely Machine learning for text used for Python, scikit-learn is an open-source, free machine learning library. It has many useful tools for stats modeling and machine learning including regression, classification, and clustering.

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Mlearning.ai

JANUARY 31, 2023

left: neutral pose — do nothing | right: fist  — close gripper | Photos from myo-readings-dataset left: extension  — move forward | right: flexion  — move backward | Photos from myo-readings-dataset This project uses the scikit-learn implementation of a Support Vector Machine (SVM) trained for gesture recognition.

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Clustering Algorithm Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 18, 2024

Ethical considerations are crucial in developing fair Machine Learning solutions. Basics of Machine Learning Machine Learning is a subset of Artificial Intelligence (AI) that allows systems to learn from data, improve from experience, and make predictions or decisions without being explicitly programmed.

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Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

Data Science 52

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ODSC - Open Data Science

JANUARY 7, 2025

Classification techniques like random forests, decision trees, and support vector machines are among the most widely used, enabling tasks such as categorizing data and building predictive models. Clustering methods are similarly important, particularly for grouping data into meaningful segments without predefined labels.

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Mlearning.ai

MAY 23, 2023

There are majorly two categories of sampling techniques based on the usage of statistics, they are: Probability Sampling techniques: Clustered sampling, Simple random sampling, and Stratified sampling. Another example can be the algorithm of a support vector machine. These are called support vectors.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

DrivenData Labs

MAY 1, 2025

Some participants combined a transformer neural network with a tree-based model or support vector machine (SVM). Cluster 0 was in English and included many people talking to an Alexa. Cluster 1 and 2 were both Spanish. Cluster 3 was Mandarin. This had a few concrete impacts. This had a few concrete impacts.

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