Data Analysis, K-nearest Neighbors and Support Vector Machines

Data Analysis

K-nearest Neighbors

Support Vector Machines

Problem-solving tools offered by digital technology

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.,

K-nearest Neighbors

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Top 8 Machine Learning Algorithms

Data Science Dojo

JULY 15, 2024

Common Classification Algorithms: Logistic Regression: A popular choice for binary classification, it uses a mathematical function to model the probability of a data point belonging to a particular class. Decision Trees: These work by asking a series of yes/no questions based on data features to classify data points.

Machine Learning

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Five machine learning types to know

IBM Journey to AI blog

DECEMBER 20, 2023

Classification algorithms —predict categorical output variables (e.g., “junk” or “not junk”) by labeling pieces of input data. Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others.

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

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

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

ODSC - Open Data Science

JANUARY 5, 2024

Without this library, data analysis wouldn’t be the same without pandas, which reign supreme with its powerful data structures and manipulation tools. Pandas provides a fast and efficient way to work with tabular data. It is widely used in data science, finance, and other fields where data analysis is essential.

Python

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Predicting Heart Failure Survival with Machine Learning Models — Part II

Towards AI

JULY 19, 2023

That post was dedicated to an exploratory data analysis while this post is geared towards building prediction models. among supervised models and k-nearest neighbors, DBSCAN, etc., Motivation The motivating question is— ‘What are the chances of survival of a heart failure patient?’. among unsupervised models.

Machine Learning

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How IDIADA optimized its intelligent chatbot with Amazon Bedrock

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

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Everything to know about Anomaly Detection in Machine Learning

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. Anomalies might have low probabilities under the fitted GMM, as they deviate from the common Gaussian patterns observed in normal data.

Machine Learning

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Basic Data Science Terms Every Data Analyst Should Know

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

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Understanding and Building Machine Learning Models

Pickl AI

NOVEMBER 18, 2024

The algorithm you select depends on the nature of the problem and the type of data you have. spam detection), you might choose algorithms like Logistic Regression , Decision Trees, or Support Vector Machines. customer segmentation), clustering algorithms like K-means or hierarchical clustering might be appropriate.

Machine Learning

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Text Classification in NLP using Cross Validation and BERT

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

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Credit Card Fraud Detection Using Spectral Clustering

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. Supervised Learning These methods require labeled data to train the model. The model learns to distinguish between normal and abnormal data points.

Clustering

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[Updated] 100+ Top Data Science Interview Questions

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

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From prediction to prevention: Machines’ struggle to save our hearts

Dataconomy

SEPTEMBER 1, 2023

So how can the technology of our time, machine learning, be used to improve the quality and length of human life? Heart disease stands as one of the foremost global causes of mortality today, presenting a critical challenge in clinical data analysis. Dealing with missing values is a common challenge in medical data analysis.

Decision Trees

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Data Science Current

Problem-solving tools offered by digital technology

Top 8 Machine Learning Algorithms

Webinars

Trending Sources

Five machine learning types to know

Webinars

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

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

Predicting Heart Failure Survival with Machine Learning Models — Part II

How IDIADA optimized its intelligent chatbot with Amazon Bedrock

Everything to know about Anomaly Detection in Machine Learning

Basic Data Science Terms Every Data Analyst Should Know

Understanding and Building Machine Learning Models

Text Classification in NLP using Cross Validation and BERT

Credit Card Fraud Detection Using Spectral Clustering

[Updated] 100+ Top Data Science Interview Questions

From prediction to prevention: Machines’ struggle to save our hearts

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