Data Science Dojo

FEBRUARY 15, 2023

Zheng’s “Guide to Data Structures and Algorithms” Parts 1 and Part 2 1) Big O Notation 2) Search 3) Sort 3)–i)–Quicksort 3)–ii–Mergesort 4) Stack 5) Queue 6) Array 7) Hash Table 8) Graph 9) Tree (e.g.,

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K-nearest Neighbors Decision Trees Support Vector Machines Algorithm 195

Data Science Dojo

MAY 27, 2024

A visual representation of discriminative AI – Source: Analytics Vidhya Discriminative modeling, often linked with supervised learning, works on categorizing existing data. Generative AI often operates in unsupervised or semi-supervised learning settings, generating new data points based on patterns learned from existing data.

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K-nearest Neighbors AI AI Supervised Learning 338

Towards AI

JULY 3, 2024

For geographical analysis, Random Forest, Support Vector Machines (SVM), and k-nearest Neighbors (k-NN) are three excellent methods. Scalability: Verify that the algorithm can manage increasing data quantities and, if required, be applied to distributed systems. So, Who Do I Have?

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K-nearest Neighbors Machine Learning Machine Learning Algorithm 79

IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning types Machine learning algorithms fall into five broad categories: supervised learning, unsupervised learning, semi-supervised learning, self-supervised and reinforcement learning. the target or outcome variable is known). temperature, salary).

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Machine Learning Machine Learning Supervised Learning Clustering 97

Pickl AI

AUGUST 28, 2024

In this blog, we will delve into the world of classification algorithms, exploring their basics, key algorithms, how they work, advanced topics, practical implementation, and the future of classification in Machine Learning. Instead, they memorise the training data and make predictions by finding the nearest neighbour.

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Machine Learning Machine Learning Algorithm K-nearest Neighbors 52

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.

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Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 91

Pickl AI

JULY 31, 2023

Understanding Eager Learning Eager Learning, also known as “Eager Supervised Learning,” is a widely used approach in Machine Learning. Examples of Eager Learning Algorithms: Logistic Regression : A classic Eager Learning algorithm used for binary classification tasks.

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Machine Learning Machine Learning K-nearest Neighbors Algorithm 52