Eqxtech.com


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Domain Informations

Eqxtech.com lookup results from whois.corporatedomains.com server:
  • Domain created: 2016-12-08T17:19:22Z
  • Domain updated: 2025-12-04T06:02:31Z
  • Domain expires: 2026-12-08T17:19:22Z 0 Years, 77 Days left
  • Website age: 9 Years, 286 Days
  • Registrar Domain ID: 2080116630_DOMAIN_COM-VRSN
  • Registrar Url: http://cscdbs.com
  • Registrar WHOIS Server: whois.corporatedomains.com
  • Registrar Abuse Contact Email: [email protected]
  • Registrar Abuse Contact Phone: 8887802723
  • Name server:
    • DNS1.CSCDNS.NET
    • DNS2.CSCDNS.NET

Network
  • 0 : 66.147.240.0 - 66.147.255.255,UNIFIEDLAYER-NETWORK-4,NET-66-147-240-0-1,Direct Allocation,2006-08-08,2025-07-24,Array
  • 1 : NETBLK-UL.66.147.240.0/20,UL-66.147.240.0/20,66.147.240.0/20,2012-11-19,2012-11-19
Owner
  • organization : Unified Layer
  • handle : BLUEH-2
  • address : Array,Provo,UT,84606,US
Abuse
Technical support
  • handle : NETWO2081-ARIN
  • name : Network Operations
  • phone : +1-801-765-9400
  • email : [email protected]
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Host Informations

  • IP address: 66.147.244.154
  • Location: Provo United States
  • Latitude: 40.2342
  • Longitude: -111.6442
  • Timezone: America/Denver

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Port Scanner (IP: 66.147.244.154)

 › Ftp: 21
 › Ssh: 22
 › Telnet: 23
 › Smtp: 25
 › Dns: 53
 › Http: 80
 › Pop3: 110
 › Portmapper, rpcbind: 111
 › Microsoft RPC services: 135
 › Netbios: 139
 › Imap: 143
 › Ldap: 389
 › Https: 443
 › SMB directly over IP: 445
 › Msa-outlook: 587
 › IIS, NFS, or listener RFS remote_file_sharing: 1025
 › Lotus notes: 1352
 › Sql server: 1433
 › Point-to-point tunnelling protocol: 1723
 › My sql: 3306
 › Remote desktop: 3389
 › Session Initiation Protocol (SIP): 5060
 › Virtual Network Computer display: 5900
 › X Window server: 6001
 › Webcache: 8080


Spam Check (IP: 66.147.244.154)

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Websites Listing

We found Websites Listing below when search with eqxtech.com on Search Engine

Profiles - Equinox | Technology

2019-03-31  · EQXTECH TEAM PROFILES: Gina Shastri. Dec 25, 2018 Liz Sams Profiles. So, why Equinox? Being that I’ve worked in consulting for almost four years, primarily working with Dynamics CRM, I thought it would be a really …

Eqxtech.com

Eqxtech Admin – Medium

Read writing from Eqxtech Admin on Medium. Every day, Eqxtech Admin and thousands of other voices read, write, and share important stories on Medium.

Medium.com

Increasing Test Coverage with Hybrid Automation …

2022-04-20  · Originally published at https://eqxtech.com on April 20, 2022 by Kunj Vegada In today’s world, people tend to browse on mobile browsers more than desktop browsers.

Medium.com

Applications of K-Means Clustering | by Eqxtech Admin

2022-05-03  · The K-mean algorithm allocates a set of data points into K clusters; the “means” part refers to the method used to calculate the centroids (centers of the clusters). Pick K based on …

Medium.com

K-Means Clustering Explained - Medium

2022-05-10  · K-means: It is an unsupervised learning algorithm used to divide input data into different predefined clusters. K is a number that defines…

Medium.com

Customer Segmentation: K-Means Clustering & A/B Testing

2020-08-16  · K-Means tries to address two questions: (1) K: the number of clusters (groups) we expect to find in the dataset and (2) Means: the average distance of data to each cluster …

Towardsdatascience.com

K Means Clustering Algorithm & its Application - Medium

2018-10-12  · K-means clustering is an unsupervised machine learning algorithm for clustering ’n’ observations into ‘k’ clusters where k is predefined or user-defined constant. The main idea is …

Medium.datadriveninvestor.com

Intuition Behind K-Means Clustering | by Rohan Roney - Medium

2021-04-29  · A collection of clothes. In simple terms, K-Means is one of the simplest clustering algorithms whose primary goal is to group similar elements or data points into a cluster. Here k …

Medium.com

K-Means Clustering — A Comprehensive Guide to Its Successful …

2021-04-25  · Elbow plot for choosing the ideal number of clusters. Image by author.. WCSS reduces as you introduce more clusters. However, after a certain point, the reduction in WCSS …

Towardsdatascience.com

K-Means Clustering in Data Mining | by Dushanthi Madhushika

2021-09-03  · K-Means clustering is considered one of the most popular unsupervised (unlabeled data are used for clustering) and hard clustering approach (data point can only belong to one …

Medium.com


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