IBM Journey to AI blog

DECEMBER 19, 2023

This type of machine learning is useful in known outlier detection but is not capable of discovering unknown anomalies or predicting future issues. Regression modeling is a statistical tool used to find the relationship between labeled data and variable data.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Mlearning.ai

JULY 6, 2023

NOTES, DEEP LEARNING, REMOTE SENSING, ADVANCED METHODS, SELF-SUPERVISED LEARNING A note of the paper I have read Photo by Kelly Sikkema on Unsplash Hi everyone, In today’s story, I would share notes I took from 32 pages of Wang et al., Hence it is possible to train the downstream task with a few labeled data.

Supervised Learning 52

Supervised Learning Deep Learning Deep Learning K-nearest Neighbors 52

AWS Machine Learning Blog

FEBRUARY 25, 2025

Its internal deployment strengthens our leadership in developing data analysis, homologation, and vehicle engineering solutions. Instead of treating each input as entirely unique, we can use a distance-based approach like k-nearest neighbors (k-NN) to assign a class based on the most similar examples surrounding the input.

Algorithm 73

Algorithm Machine Learning Machine Learning K-nearest Neighbors 73

AWS Machine Learning Blog

APRIL 5, 2023

k-NN index query – This is the inference phase of the application. In this phase, you submit a text search query or image search query through the deep learning model (CLIP) to encode as embeddings. Then, you use those embeddings to query the reference k-NN index stored in OpenSearch Service.

ML 109

ML ML AWS K-nearest Neighbors 109

Pickl AI

SEPTEMBER 3, 2023

49% of companies in the world that use Machine Learning and AI in their marketing and sales processes apply it to identify the prospects of sales. An ensemble of decision trees is trained on both normal and anomalous data. Anomalies might lead to deviations from the normal patterns the model has learned.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

PyImageSearch

SEPTEMBER 16, 2024

Anomaly detection ( Figure 2 ) is a critical technique in data analysis used to identify data points, events, or observations that deviate significantly from the norm. Similarly, autoencoders can be trained to reconstruct input data, and data points with high reconstruction errors can be flagged as anomalies.

Clustering 56

Clustering Algorithm Machine Learning Machine Learning 56

Mlearning.ai

FEBRUARY 15, 2023

K-Nearest Neighbou r: The k-Nearest Neighbor algorithm has a simple concept behind it. The method seeks the k nearest neighbours among the training documents to classify a new document and uses the categories of the k nearest neighbours to weight the category candidates [3].

Cross Validation 52

Cross Validation Decision Trees Algorithm Natural Language Processing 52

Pickl AI

SEPTEMBER 12, 2024

Data Cleaning: Raw data often contains errors, inconsistencies, and missing values. Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Visualisation: Effective communication of insights is crucial in Data Science.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 18, 2024

K-Nearest Neighbors), while others can handle large datasets efficiently (e.g., On the other hand, overfitting arises when a model is too complex, learning noise and irrelevant details rather than generalisable trends. It offers extensive support for Machine Learning, data analysis, and visualisation.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 52

Mlearning.ai

MAY 23, 2023

The following Venn diagram depicts the difference between data science and data analytics clearly: 3. Data analysis can not be done on a whole volume of data at a time especially when it involves larger datasets. The K-Nearest Neighbor Algorithm is a good example of an algorithm with low bias and high variance.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52