Smart Data Collective

SEPTEMBER 17, 2020

One new feature is the ability to create a radius, which wouldn’t be possible without the highly refined data mining and analytics features embedded in the core of the Google Maps algorithm. In 2012, Google boasted about its capabilities of using big data to create storytelling via interactive maps.

Big Data 134

Big Data Big Data Data Mining Data Mining 134

Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

Natural Language Processing 98

Natural Language Processing Algorithm Machine Learning Machine Learning 98

O'Reilly Media

SEPTEMBER 19, 2023

A basic, production-ready cluster priced out to the low-six-figures. A company then needed to train up their ops team to manage the cluster, and their analysts to express their ideas in MapReduce. Plus there was all of the infrastructure to push data into the cluster in the first place. And, often, to giving up. Goodbye, Hadoop.

Hadoop 101

Hadoop Algorithm ML ML 101

AWS Machine Learning Blog

AUGUST 22, 2023

Many ML algorithms train over large datasets, generalizing patterns it finds in the data and inferring results from those patterns as new unseen records are processed. Flower has an extensive implementation of FL averaging algorithms and a robust communication stack. Each account or Region has its own training instances.

Machine Learning 92

Machine Learning Machine Learning AWS ML 92

AWS Machine Learning Blog

SEPTEMBER 11, 2024

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. in 2012 is now widely referred to as ML’s “Cambrian Explosion.” In summary, the Neuron SDK allows developers to easily parallelize ML algorithms, such as those commonly found in FSI.

AWS 113

AWS ML ML Clustering 113

AWS Machine Learning Blog

NOVEMBER 13, 2024

To search against the database, you can use a vector search, which is performed using the k-nearest neighbors (k-NN) algorithm. When you perform a search, the algorithm computes a similarity score between the query vector and the vectors of stored objects using methods such as cosine similarity or Euclidean distance.

AWS 125

AWS Database K-nearest Neighbors AI 125

Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., 2012; Otsu, 1979; Long et al., The MBD algorithm then searches for a subset of nodes (i.e., 2018; Sitawarin et al., 2015; Huang et al.,

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52