Tweag

APRIL 19, 2023

Detecting cancerous cells in microscopic photography of cells (Whole Slide Images, aka WSIs) is usually done with segmentation algorithms, which NNs are very good at. Marini et al This results in a very large amount of data for a single slide, often a few gigabytes per slide, which is all stored in one big file.

Medical 60

Medical Process Cloud Bytes 60

Knowledge Hut

NOVEMBER 16, 2023

More and more companies are focusing on hiring data scientists to help them unlock the true potential of their businesses and channelize maximum profits. A data scientist is a person expert in analytics, especially gathering and evaluating large chunks of structured and unstructured data to find trends and proper data management.

IT 52

IT Software Engineer Software Engineering Cloud Computing 52

Knowledge Hut

DECEMBER 27, 2023

Many business owners and professionals are interested in harnessing the power locked in Big Data using Hadoop often pursue Big Data and Hadoop Training. What is Big Data? Big data is often denoted as three V’s: Volume, Variety and Velocity. We will discuss more on this later in this article.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

ProjectPro

JUNE 1, 2017

(Source : [link] ) Medical big data to be pooled for disease research and drug development in Japan. QSS is a deep learning product and service offering by the popular hadoop vendor that will enable the training of compute intensive deep learning algorithms. Source - [link] ) The siren song of Hadoop.ComputerWorld.com, May 23, 2017.

Hadoop 52

Hadoop Medical Pipeline-centric Database-centric 52

Knowledge Hut

DECEMBER 27, 2023

An MBA in Hospitality and Tourism is one wise choice to go for. A career in Data Science Data Science is a study interrelated and disciplinary field that employs maths, science algorithms, advanced analytics, and Artificial Intelligence(AI). In recent years, the demand for Data Scientists has grown on a huge scale.

Banking 52

Banking Finance Recruitment Portfolio 52

ProjectPro

FEBRUARY 8, 2017

However, this does not mean just Hadoop but Hadoop along with other big data technologies like in-memory frameworks, data marts, discovery tools ,data warehouses and others that are required to deliver the data to the right place at right time.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

AltexSoft

MAY 5, 2023

AI in a nutshell Artificial Intelligence (AI) , at its core, is a branch of computer science that focuses on developing algorithms and computer systems capable of performing tasks that typically require human intelligence. Deep Learning is a subset of machine learning that focuses on building complex algorithms named deep neural networks.

Machine Learning 59

Machine Learning Hospitality Algorithm Deep Learning 59

ProjectPro

MARCH 15, 2016

Such large commercial banks can leverage big data analytics more effectively by using frameworks like Hadoop on massive volumes of structured and unstructured data. Hadoop allows us to store data that we never stored before. Big Data and Hadoop technology is also applied in the Healthcare Insurance Business.

Hadoop 40

Hadoop Retail Healthcare Banking 40

AltexSoft

FEBRUARY 21, 2023

This blog post will delve into the challenges, approaches, and algorithms involved in hotel price prediction. Hotel price prediction is the process of using machine learning algorithms to forecast the rates of hotel rooms based on various factors such as date, location, room type, demand, and historical prices.

Hospitality 52

Hospitality Datasets Algorithm Machine Learning 52

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

JUNE 26, 2023

Note that in many cases, the process of gathering information never ends since you always need fresh data to re-train and improve existing ML models, gain consumer insights, analyze current market trends, and so on. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

U-Next

SEPTEMBER 22, 2022

Several vetted models and algorithms are used in the predictive analytics tools in order to generate a large number of useful outcomes that are applicable to a wide range of use cases. . An evaluation of a sequence of data points over a period of time is carried out using this model. Types Of Predictive Models . Random Forest .

Hospitality 40

Hospitality Algorithm Machine Learning Banking 40

AltexSoft

SEPTEMBER 21, 2023

These indices are specially designed data structures that map out the data for rapid searches, allowing for the retrieval of queries in milliseconds. As a result, Elasticsearch is exceptionally efficient in managing structured and unstructured data. Real-time behavior modeling with ML. Business workflow automation.

Engineering 52

Engineering NoSQL Programming Language Java 52

AltexSoft

DECEMBER 15, 2021

On the surface, ML algorithms take the data, develop their own understanding of it, and generate valuable business insights and predictions — all without human intervention. It boosts the performance of ML specialists relieving them of repetitive tasks and enables even non-experts to experiment with smart algorithms.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59