Топ-10 конкурентов datasemantics.co

incontextsolutions.com

ShopperMX, retail's all-in-one visualization and collaboration tool to maximize ROI, grow revenue and move at the speed of the marketplace.

velvetech.com

Velvetech is a US-based full-cycle software development company with 20+ years of experience delivering custom solutions for SMBs, enterprises, & startups.

signl4.com

Discover how IoT Service Alerting with SIGNL4 improves response time and enables targeted notifications for IoT systems.

ariseanalytics.com

TECH BLOG | 国内最大規模のデータと最先端のデータ処理・分析技術をもつデータサイエンティスト集団、株式会社ARISE analytics（アライズ アナリティクス）の技術情報を掲載します。

softwebsolutions.com

How to choose the right machine learning model from supervised and unsupervised learning to reinforcement and deep learning, examples, algorithms, and applications.

pragmatiq.co.uk

Visualise data, gain valuable insights and make informed, strategic decisions with this business intelligence solution.

metisbi.co.uk

Enhance manufacturing operations with Power BI manufacturing dashboards for data-driven insights. Book a free demo and discovery call to see it in action!

brainforge.ai

Learn how to set up Amplitude tracking the right way. Avoid data mess with our step-by-step guide to event tracking and user behavior analytics.

mopinion.com

Mopinion Policies For legal purposes, these documents are only available in English.

g-stat.com

academic research - introductionThe Effect of machine learning algorithms Advancement Level over their performance when solving Business Analytics problems October 2019 Yossi HohashviliAcademic adviser:  Adir Even, PhD, Ben-Gurion university of the NegevAdditional adviser: Ephraim Goldin, CEO and founder, G-statAbstractOne of the most severe problems in Business Analytics (BA) is automation of decision-making processes. this automation is of great relevance do to the pros and cons that may accrue using a specific methodology. at a time where data, technology and analytics occupy a major place in the business sector, organization's ability to keep pace with the technological development of the big data world is critical. For this reason, the management team must identify an optimal alternative for solving a BA problem. In order that the director will make an optimal decision, he must identify the type of problem, tools and resources at his disposal to achieve the purpose of the business. The inability of an organization to make correct and reasonable strategic decisions that consider technological development may cause the organization to fail in its objectives.In recent years, advanced Machine Learning (ML) algorithms such as Deep Learning (DL) has been empirically proven themselves superior to traditional ML and classical statistics algorithms for solving unstructured data problems, such as image, text and sound processing. On the other hand, there are few studies that regards the superiority of DL over other algorithms mentioned above or advanced ones such as XGboost, when tackling problems with structured data, which is known to characterize business information to a large extent. The following research will examine the possibility of expanding the scope of learning algorithms used for BA problems with the use of advanced algorithms for solving complex classification and regression problems that characterize the BA world. we will achieve this, by conducting an ex