Data Science Dojo

AUGUST 19, 2024

This is used for tasks like clustering, dimensionality reduction, and anomaly detection. For example, clustering customers based on their purchase history to identify different customer segments. Reinforcement learning: This involves training an agent to make decisions in an environment to maximize a reward signal.

AI 305

AI AI Machine Learning Machine Learning 305

IBM Journey to AI blog

AUGUST 9, 2024

Predictive AI is its own class of artificial intelligence , and while it might be a lesser-known approach, it’s still a powerful tool for businesses. Decision trees implement a divide-and-conquer splitting strategy for optimal classification. But generative AI is not predictive AI. What is generative AI?

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Pickl AI

OCTOBER 24, 2024

Summary: This article compares Artificial Intelligence (AI) vs Machine Learning (ML), clarifying their definitions, applications, and key differences. While AI aims to replicate human intelligence across various domains, ML focuses on learning from data to improve performance. What is Artificial Intelligence?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Mlearning.ai

NOVEMBER 3, 2023

AI-generated image ( craiyon ) [link] Who By Prior And who by prior, who by Bayesian Who in the pipeline, who in the cloud again Who by high dimension, who by decision tree Who in your many-many weights of net Who by very slow convergence And who shall I say is boosting? I think I managed to get most of the ML players in there…??

Machine Learning 98

Machine Learning Machine Learning Decision Trees Deep Learning 98

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. Naïve Bayes algorithms include decision trees , which can actually accommodate both regression and classification algorithms.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

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. Machine Learning Supervised Learning includes algorithms like linear regression, decision trees, and support vector machines.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

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 91

K-nearest Neighbors Decision Trees AI AI 91

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

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. The most common unsupervised algorithms are clustering, dimensionality reduction, and association rule mining.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

Dataconomy

JUNE 13, 2023

In this era of information overload, utilizing the power of data and technology has become paramount to drive effective decision-making. Decision intelligence is an innovative approach that blends the realms of data analysis, artificial intelligence, and human judgment to empower businesses with actionable insights.

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Power BI Data Analysis Data Analysis Artificial Intelligence 103

ODSC - Open Data Science

MAY 31, 2023

From there, a machine learning framework like TensorFlow, H2O, or Spark MLlib uses the historical data to train analytic models with algorithms like decision trees, clustering, or neural networks. Tiered Storage enables long-term storage with low cost and the ability to more easily operate large Kafka clusters.

Data Lakes 131

Data Lakes Machine Learning Machine Learning Apache Kafka 131

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.

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K-nearest Neighbors Machine Learning Machine Learning Decision Trees 81

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

Pickl AI

APRIL 3, 2023

Accordingly, Examples of Supervised learning include linear regression, logistic regression , decision trees, random forests and neural networks. Significantly, there are two types of Unsupervised Learning: Clustering: which involves grouping similar data points together. Additionally, Supervised learning predicts the output.

Supervised Learning 52

Supervised Learning Machine Learning Machine Learning Clustering 52

Towards AI

SEPTEMBER 5, 2024

It offers pure NumPy implementations of fundamental machine learning algorithms for classification, clustering, preprocessing, and regression. From linear regression to decision trees, these algorithms are the building blocks of ML. This repo is designed for educational exploration.

Algorithm 85

Algorithm ML ML Machine Learning 85

Pickl AI

NOVEMBER 5, 2024

Introduction Data Science and Artificial Intelligence (AI) are at the forefront of technological innovation, fundamentally transforming industries and everyday life. What is Data Science and Artificial Intelligence? The impact is profound and far-reaching.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 52

Dataconomy

AUGUST 9, 2023

But as in every aspect of our lives, Machine Learning algorithms and artificial intelligence help us in network traffic analysis. Clustering can help in identifying patterns and anomalies within specific groups What are the best machine learning tools to analyze network traffic?

Machine Learning 91

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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. Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

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. Clustering and dimensionality reduction are common tasks in unSupervised Learning.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

ODSC - Open Data Science

AUGUST 15, 2023

You’ll get hands-on practice with unsupervised learning techniques, such as K-Means clustering, and classification algorithms like decision trees and random forest. Finally, you’ll explore how to handle missing values and training and validating your models using PySpark.

Machine Learning 52

Machine Learning Machine Learning Data Science Data Scientist 52

Pickl AI

FEBRUARY 7, 2025

While both are subsets of Artificial Intelligence, they differ significantly regarding techniques and applications. Machine Learning (ML) is a subset of Artificial Intelligence (AI) that enables machines to improve their task performance by learning from data rather than following explicit instructions.

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Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

JULY 10, 2023

Hence, you can use R for classification, clustering, statistical tests and linear and non-linear modelling. Packages like caret, random Forest, glmnet, and xgboost offer implementations of various machine learning algorithms, including classification, regression, clustering, and dimensionality reduction. How is R Used in Data Science?

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

PyImageSearch

OCTOBER 21, 2024

In the first part of our Anomaly Detection 101 series, we learned the fundamentals of Anomaly Detection and saw how spectral clustering can be used for credit card fraud detection. On Lines 21-27 , we define a Node class, which represents a node in a decision tree. We first start by defining the Node of an iTree.

Algorithm 102

Algorithm Deep Learning Deep Learning Data Preparation 102

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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Big Data Big Data Big Data Analytics Big Data Analytics 52

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

Data Science Python Data Scientist Machine Learning 52

AWS Machine Learning Blog

OCTOBER 30, 2024

These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval. Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning.

Machine Learning 90

Machine Learning Machine Learning AWS Data Scientist 90

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. Decision trees are more prone to overfitting. Some algorithms that have low bias are Decision Trees, SVM, etc.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

Machine learning is a subset of artificial intelligence that enables computers to learn from data and improve over time without being explicitly programmed. Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

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.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Data Science Dojo

AUGUST 30, 2023

It is at the forefront of artificial intelligence, driving the decision-making process of businesses, governments, and organizations worldwide. It leverages algorithms to parse data, learn from it, and make predictions or decisions without being explicitly programmed.

Data Science 195

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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 91

Machine Learning Machine Learning Algorithm K-nearest Neighbors 91

How to Learn Machine Learning

MARCH 25, 2025

Some common supervised learning algorithms include decision trees, random forests, support vector machines, and linear regression. These algorithms help businesses make decisions when there is clear historical data available. For instance, marketing teams use clustering techniques to segment customers based on buying behavior.

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Supervised Learning Machine Learning Machine Learning Algorithm 59