ODSC - Open Data Science

JANUARY 5, 2024

If you’re looking to start building up your skills in these important Python libraries, especially for those that are used in machine & deep learning, NLP, and analytics, then be sure to check out everything that ODSC East has to offer. And did any of your favorites make it in?

Python 52

Python K-nearest Neighbors Data Science Data Visualization 52

AWS Machine Learning Blog

FEBRUARY 25, 2025

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. To make this work, we need to transform the textual interactions into a format that allows algebraic operations.

Algorithm 71

Algorithm Machine Learning Machine Learning K-nearest Neighbors 71

Pickl AI

SEPTEMBER 3, 2023

Supervised Anomaly Detection: Support Vector Machines (SVM): In a supervised context, SVM is trained to find a hyperplane that best separates normal instances from anomalies. k-Nearest Neighbors (k-NN): In the supervised approach, k-NN assigns labels to instances based on their k-nearest neighbours.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Pickl AI

DECEMBER 9, 2024

Algorithmic Bias Algorithmic bias arises from the design of the learning algorithm itself. Every Machine Learning algorithm, whether a decision tree, support vector machine, or deep neural network, inherently favours certain solutions over others. A high-bias model (e.g., The key is finding a balance.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Natural Language Processing 52

Pickl AI

JULY 26, 2023

Highly Flexible Neural Networks Deep neural networks with a large number of layers and parameters have the potential to memorize the training data, resulting in high variance. K-Nearest Neighbors with Small k I n the k-nearest neighbours algorithm, choosing a small value of k can lead to high variance.

Machine Learning 52

Machine Learning Machine Learning Cross Validation Decision Trees 52

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

PyImageSearch

SEPTEMBER 16, 2024

Supervised Learning These methods require labeled data to train the model. The model learns to distinguish between normal and abnormal data points. For example, in fraud detection, SVM (support vector machine) can classify transactions as fraudulent or non-fraudulent based on historically labeled data.

Clustering 56

Clustering Algorithm Machine Learning Machine Learning 56

Pickl AI

NOVEMBER 18, 2024

spam detection), you might choose algorithms like Logistic Regression , Decision Trees, or Support Vector Machines. For unSupervised Learning tasks (e.g., customer segmentation), clustering algorithms like K-means or hierarchical clustering might be appropriate. For instance: For a classification problem (e.g.,

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

DagsHub

DECEMBER 23, 2024

Key Characteristics Static Dataset : Works with a predefined set of unlabeled examples Batch Selection : Can select multiple samples simultaneously for labeling because of which it is widely used by deep learning models. Pool-Based Active Learning Scenario : Classifying images of artwork styles for a digital archive.  

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Clustering 52

Mlearning.ai

MAY 23, 2023

Trade-off Of Bias And Variance: So, as we know that bias and variance, both are errors in machine learning models, it is very essential that any machine learning model has low variance as well as a low bias so that it can achieve good performance. Another example can be the algorithm of a support vector machine.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks. Deep Learning : A subset of Machine Learning that uses Artificial Neural Networks with multiple hidden layers to learn from complex, high-dimensional data.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52