Data Science Dojo

FEBRUARY 14, 2024

In the world of data science and machine learning, feature transformation plays a crucial role in achieving accurate and reliable results. Normalization A feature scaling technique is often applied as part of data preparation for machine learning.

K-nearest Neighbors 243

K-nearest Neighbors Machine Learning Machine Learning Support Vector Machines 243

Dataconomy

MARCH 4, 2025

It’s an integral part of data analytics and plays a crucial role in data science. By utilizing algorithms and statistical models, data mining transforms raw data into actionable insights. Each stage is crucial for deriving meaningful insights from data.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

AWS Machine Learning Blog

SEPTEMBER 25, 2024

Solution overview In this solution, we start with data preparation, where the raw datasets can be stored in an Amazon Simple Storage Service (Amazon S3) bucket. We provide a Jupyter notebook to preprocess the raw data and use the Amazon Titan Multimodal Embeddings model to convert the image and text into embedding vectors.

AWS 93

AWS K-nearest Neighbors ML ML 93

PyImageSearch

SEPTEMBER 16, 2024

Similarly, autoencoders can be trained to reconstruct input data, and data points with high reconstruction errors can be flagged as anomalies. Proximity-Based Methods Proximity-based methods can detect anomalies based on the distance between data points. We will start by setting up libraries and data preparation.

Clustering 57

Clustering Algorithm Machine Learning Machine Learning 57

The MLOps Blog

DECEMBER 19, 2022

However, Data Preparation, Data Sampling Strategy, selection of appropriate Distance Metrics, selection of the appropriate Loss function, and the structure of the network determine the performance of these models as well. index.add(xb) # xq are query vectors, for which we need to search in xb to find the k nearest neighbors. #

ML 52

ML ML Algorithm Deep Learning 52

Towards AI

JULY 19, 2023

Check out the previous post to get a primer on the terms used) Outline Dealing with Class Imbalance Choosing a Machine Learning model Measures of Performance Data Preparation Stratified k-fold Cross-Validation Model Building Consolidating Results 1. among supervised models and k-nearest neighbors, DBSCAN, etc.,

Machine Learning 40

Machine Learning Machine Learning K-nearest Neighbors Support Vector Machines 40