Artificial Intelligence, Decision Trees and K-nearest Neighbors

Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

MAY 27, 2024

In the recent discussion and advancements surrounding artificial intelligence, there’s a notable dialogue between discriminative and generative AI approaches. These methodologies represent distinct paradigms in AI, each with unique capabilities and applications.

K-nearest Neighbors

K-nearest Neighbors Supervised Learning AI AI

Machine learning algorithms

Dataconomy

MARCH 28, 2025

Their application spans a wide array of tasks, from categorizing information to predicting future trends, making them an essential component of modern artificial intelligence. Machine learning algorithms are specialized computational models designed to analyze data, recognize patterns, and make informed predictions or decisions.

Machine Learning

Machine Learning Machine Learning Algorithm K-nearest Neighbors

From Pixels to Places: Harnessing Geospatial Data with Machine Learning.

Towards AI

APRIL 4, 2024

According to IBM, machine learning is a subfield of computer science and artificial intelligence (AI) that focuses on using data and algorithms to simulate human learning processes while progressively increasing their accuracy.

K-nearest Neighbors

K-nearest Neighbors Machine Learning Machine Learning Decision Trees

Everything you should know about AI models

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?

K-nearest Neighbors

K-nearest Neighbors Decision Trees AI AI

Everything you should know about AI models

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?

K-nearest Neighbors

K-nearest Neighbors Decision Trees AI AI

Five machine learning types to know

IBM Journey to AI blog

DECEMBER 20, 2023

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.

Machine Learning

Machine Learning Machine Learning Supervised Learning Clustering

Machine learning world easy-to-understand overview for beginners

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.

Machine Learning

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

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

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors

How to Choose the Best Algorithm for Your Machine Learning Project

Mlearning.ai

APRIL 6, 2023

For example, if you have binary or categorical data, you may want to consider using algorithms such as Logistic Regression, Decision Trees, or Random Forests. In contrast, for datasets with low dimensionality, simpler algorithms such as Naive Bayes or K-Nearest Neighbors may be sufficient.

Machine Learning

Machine Learning Machine Learning Algorithm Decision Trees

8 of the Top Python Libraries You Should be Using in 2024

ODSC - Open Data Science

JANUARY 5, 2024

Scikit-learn is also open-source, which makes it a popular choice for both academic and commercial use.

Python

Python K-nearest Neighbors Data Science Data Visualization

Basic Data Science Terms Every Data Analyst Should Know

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. Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks.

Data Analyst

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Understanding and Building Machine Learning Models

Pickl AI

NOVEMBER 18, 2024

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. Decision trees are easy to interpret but prone to overfitting. Random Forests).

Machine Learning

Machine Learning Machine Learning Algorithm Decision Trees

Text Classification in NLP using Cross Validation and BERT

Mlearning.ai

FEBRUARY 15, 2023

Some important things that were considered during these selections were: Random Forest : The ultimate feature importance in a Random forest is the average of all decision tree feature importance. A random forest is an ensemble classifier that makes predictions using a variety of decision trees.

Cross Validation

Cross Validation Decision Trees Algorithm Natural Language Processing

[Updated] 100+ Top Data Science Interview Questions

Mlearning.ai

MAY 23, 2023

Decision trees are more prone to overfitting. Some algorithms that have low bias are Decision Trees, SVM, etc. The K-Nearest Neighbor Algorithm is a good example of an algorithm with low bias and high variance. So, this is how we draw a typical decision tree. Let us see some examples.

Data Science

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Data Science Current

Generative vs Discriminative AI: Understanding the 5 Key Differences

Machine learning algorithms

Trending Sources

From Pixels to Places: Harnessing Geospatial Data with Machine Learning.

Everything you should know about AI models

Everything you should know about AI models

Five machine learning types to know

Machine learning world easy-to-understand overview for beginners

Anomaly detection in machine learning: Finding outliers for optimization of business functions

How to Choose the Best Algorithm for Your Machine Learning Project

8 of the Top Python Libraries You Should be Using in 2024

Basic Data Science Terms Every Data Analyst Should Know

Understanding and Building Machine Learning Models

Text Classification in NLP using Cross Validation and BERT

[Updated] 100+ Top Data Science Interview Questions

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