Clustering - Introduction, Areas & Applications (with examples)

In this video, we will cover the introduction of Clustering in Machine Learning, then we will understand the concept of clustering with the help of an example. Finally, we understand the areas and applications of clustering in this video. The code for the video (if any) can be found on GitHub. #machinelearning

#machine learning #machine-learning #ai

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Clustering - Introduction, Areas & Applications (with examples)

3 Examples Of Design Applications With Great UX

When it comes to design, it has long been said that simplicity is key. And although I always understood the basis for this saying, I never fully appreciated what it really meant.

As a beginner it is natural to want to show all your ability by wowing your audience. And as a teacher I see my students making this mistake often. They try to build out features as much as possible and try to showcase every aspect of their ability. As many of you know, this approach does not always result in the most aesthetically pleasing design, let alone the most user friendly experience. This is why I have stressed the importance of simplicity to all my students from the first day I started teaching.

For our latest project, I assigned teams of 4 to each create a prototype for a design application.

#design #web-design #hackernoon-top-story #ux #good-ux-design-examples #good-ui-design-examples #web-application-ui-examples #web-application-design-example

Gerhard  Brink

Gerhard Brink

1624006278

The Rising Value of Big Data in Application Monitoring

In an ecosystem that has become increasingly integrated with huge chunks of data and information traveling through the airwaves, Big Data has become irreplaceable for establishments.

From day-to-day business operations to detailed customer interactions, many ventures heavily invest in data sciences and data analysis  to find breakthroughs and marketable insights.

Plus, surviving in the current era, mandates taking informed decisions and surgical precision based on the projected forecast of current trends to retain profitability. Hence these days, data is revered as the most valuable resource.

According to a recent study by Sigma Computing , the world of Big Data is only projected to grow bigger, and by 2025 it is estimated that the global data-sphere will grow to reach 17.5 Zettabytes. FYI one Zettabyte is equal to 1 million Petabytes.

Moreover, the Big Data industry will be worth an estimate of $77 billion by 2023. Furthermore, the Banking sector generates unparalleled quantities of data, with the amount of data generated by the financial industry each second growing by 700% in 2021.

In light of this information, let’s take a quick look at some of the ways application monitoring can use Big Data, along with its growing importance and impact.

#ai in business #ai application #application monitoring #big data #the rising value of big data in application monitoring #application monitoring

Elton  Bogan

Elton Bogan

1600190040

SciPy Cluster - K-Means Clustering and Hierarchical Clustering

SciPy is the most efficient open-source library in python. The main purpose is to compute mathematical and scientific problems. There are many sub-packages in SciPy which further increases its functionality. This is a very important package for data interpretation. We can segregate clusters from the data set. We can perform clustering using a single or multi-cluster. Initially, we generate the data set. Then we perform clustering on the data set. Let us learn more SciPy Clusters.

K-means Clustering

It is a method that can employ to determine clusters and their center. We can use this process on the raw data set. We can define a cluster when the points inside the cluster have the minimum distance when we compare it to points outside the cluster. The k-means method operates in two steps, given an initial set of k-centers,

  • We define the cluster data points for the given cluster center. The points are such that they are closer to the cluster center than any other center.
  • We then calculate the mean for all the data points. The mean value then becomes the new cluster center.

The process iterates until the center value becomes constant. We then fix and assign the center value. The implementation of this process is very accurate using the SciPy library.

#numpy tutorials #clustering in scipy #k-means clustering in scipy #scipy clusters #numpy

Willa Anderson

Willa Anderson

1605791076

Here Are The Features That A Cloud Based SaaS Application Requires

Fast setup and slick UIs create incredible first impressions on users. However, enterprise managers are aware of the fact that they are at the tip of the iceberg. One of the features of a SaaS is interoperability, and such aspects are the ones that business owners need to lay a solid foundation.

Are you aware of the term “Software as a Service (SaaS)?” You probably heard it several times, but you may not know what it’s all about. Well, a SaaS, designed by a cloud-based application development company, is a cloud-based service that helps consumers gain access to software applications over the web. These applications remain hosted on the cloud and used for various purposes by companies as well as individuals.

SaaS created by a cloud-based application development company is the best alternative to traditional software installation systems. You may compare it with a TV channel that’s available for subscription. The user connects to a remotely-located base on a central server and uses a license to access data.

In other words, SaaS offers a method of software delivery by which you can access data from any device connected to the internet. Of course, this particular device should have a web browser. Software vendors host everything associated with the application, including servers, code, and databases.

Explore more: https://www.moontechnolabs.com/blog/here-are-the-features-that-a-cloud-based-saas-application-requires/

#mobile-application-development #cloud-based-saas-application #on-demand-applications #moontechnolabs #application-development-services

Cayla  Erdman

Cayla Erdman

1594369800

Introduction to Structured Query Language SQL pdf

SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.

Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:

1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.

2. Every database seller needs an approach to separate its item from others.

Right now, contrasts are noted where fitting.

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