Towards AI

JANUARY 26, 2024

For example, in the training of deep learning models, the weights and biases can be considered as model parameters. For example, in the training of deep learning models, the hyperparameters are the number of layers, the number of neurons in each layer, the activation function, the dropout rate, etc.

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K-nearest Neighbors Deep Learning Deep Learning Algorithm 93

Towards AI

APRIL 14, 2023

The prediction is then done using a k-nearest neighbor method within the embedding space. Correctly predicting the tags of the questions is a very challenging problem as it involves the prediction of a large number of labels among several hundred thousand possible labels.

K-nearest Neighbors 94

K-nearest Neighbors Algorithm Clustering Support Vector Machines 94

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. Unsupervised learning Unsupervised learning techniques do not require labeled data and can handle more complex data sets.

Machine Learning 71

Machine Learning Machine Learning Supervised 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

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

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

IBM Journey to AI blog

DECEMBER 20, 2023

Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others. They’re also part of a family of generative learning algorithms that model the input distribution of a given class or/category.

Machine Learning 81

Machine Learning Machine Learning Supervised Learning Clustering 81