Flipboard

NOVEMBER 17, 2023

Vector data is a type of data that represents a point in a high-dimensional space. This type of data is often used in ML and artificial intelligence applications. MongoDB Atlas Vector Search uses a technique called k-nearest neighbors (k-NN) to search for similar vectors.

K-nearest Neighbors

Snorkel AI

APRIL 11, 2023

I’m Cody Coleman and I’m really excited to share my research on how careful data selection can make ML development faster, cheaper, and better by focusing on quality rather than quantity. So we waste a lot of time, money, and just energy on data points that aren’t actually valuable. AB : Got it. Thank you.

K-nearest Neighbors

Snorkel AI

APRIL 11, 2023

I’m Cody Coleman and I’m really excited to share my research on how careful data selection can make ML development faster, cheaper, and better by focusing on quality rather than quantity. So we waste a lot of time, money, and just energy on data points that aren’t actually valuable. AB : Got it. Thank you.

K-nearest Neighbors

Snorkel AI

APRIL 11, 2023

I’m Cody Coleman and I’m really excited to share my research on how careful data selection can make ML development faster, cheaper, and better by focusing on quality rather than quantity. So we waste a lot of time, money, and just energy on data points that aren’t actually valuable. AB : Got it. Thank you.

K-nearest Neighbors

Mlearning.ai

JULY 6, 2023

Some common quantitative evaluations are linear probing , K nearest neighbors (KNN), and fine-tuning. Multi-modal/temporal data is one of the important aspects of remote sensing and deep learning. It allows us to perform big data analysis. Thus, it is better to begin with a general one.

Supervised Learning

Mlearning.ai

NOVEMBER 29, 2023

K-Nearest Neighbor Regression Neural Network (KNN) The k-nearest neighbor (k-NN) algorithm is one of the most popular non-parametric approaches used for classification, and it has been extended to regression.

Machine Learning

Mlearning.ai

MAY 23, 2023

The K-Nearest Neighbor Algorithm is a good example of an algorithm with low bias and high variance. This trade-off can easily be reversed by increasing the k value which in turn results in increasing the number of neighbours. This data can be used to pass as an input to the neural network maintaining a small batch size.

Data Science