#onlinebackup

[freshpc-computer-service-hu-blog]

Je computer of laptop kan soms behoorlijk vol raken met verschillende bestanden, die vaak niet eens zichtbaar zijn. Een te volle computer werkt traag en daar wordt niemand vrolijk van. Wij bieden oplossingen om je computer te ontdoen van overtollige bestanden, malware en andere bestanden die de prestaties belemmeren. Laat ons je computer onder handen nemen zodat jij weer snel kunt werken!

Neem contact op met een servicepunt in jouw buurt en ontdek zelf het verschil: https://www.freshpc.nl/servicepunt-freshpc/

FreshPC Computer Service Huissen ☎️06 3451 5782

[izoecloudservices]

Introduction- iZoe

Simplify, Optimize, Deliver

iZoe- Revolutionizing business tech with tailored, innovative solutions.

Seasoned IT professionals with diverse sector experience, delivering top-notch IT services

Specialized services - Akounter Cloud, Akounter CRM, Backup Solutions, Tally on Cloud

Our Vision: Delivering effective, efficient, and smart tech solutions.

Our Mission: Providing proactive and cost-efficient IT solutions for client success.

Your pathway to smarter, faster, and more reliable Business Operations!

[stormellc]

Dive into the enchanting world of AI-generated shows as StorMe® brings your content to life in ways you've never imagined. Witness the magic of artificial intelligence enhancing your photos and videos, creating visually stunning productions that tell the unique story of your best life.

[bemarketers]

🔐 Your Data Deserves Better

This Wednesday, we’re diving into the future of data protection with an exclusive presentation on GotBackup — the cloud backup service that secures your files and helps you earn residual income. 💻💰

🌍 100% Online & Free 🗓️ Don’t miss it — spots are limited!

👉 Reserve Your Spot Now 

https://bit.ly/42JEDax

#GotBackup #DataProtection #CloudBackup #DigitalSecurity #OnlineBackup #PassiveIncome #WorkFromHome #TechTools #BackupSolutions #SecureYourFiles #ProtectYourData #TumblrEvents #CyberSecurity #CloudStorage

(via 🔒 Why You Can’t Miss This Wednesday’s GotBackup Presentation!)

[notehowto]

How to Clear iCloud Storage: A Comprehensive Guide to Clearing Space

[evrrrrrrrr]

How Cloud Backup Can Help In Ransomware Protection?

The cases of ransomware attacks are common these days. But it doesn’t mean you can’t do anything about it. Ransomware attacks happen because of the loopholes present in your system. You can stop data loss by identifying those loopholes and taking proactive measures. Cloud backup is one of the proactive measures that you can adopt. Having your data backup on Cloud eliminates the internal risk of data theft. 

Cloud Backup Ensures Business Continuity In Bad Times

Preventing every piece of malware from accessing your network may not be in your hand, but securing your sensitive data is in your hand for sure. A regular cloud backup routine is the heart of every modern recovery plan for disasters. Ideally, it should operate continuously in the background. In the case of a ransomware infestation, hardware can be reset, and data can be recovered. Cloud backup is efficient as it assures that your data is not restricted to your premises. An attacker who gets network access cannot destroy your backup data by any means. The online backups of your cloud providers are located behind another layer of protection, guaranteeing that they are ready to recover. Even the repercussions from physical server failures can be minimized quickly. 

Cloud Backup Reduces Human Mistakes & Offers Top-Notch Security

Most businesses rely on their IT departments or even employees to back up their data. These long-lasting and laborious operations are readily ignored. Even if data are recorded, catastrophe recovery cannot be easily identifiable, located and utilized. An automated solution makes the procedure easier. By partnering with the top cloud backup services providers, you can get full data recovery within minutes. It allows you to quickly restore key services while also freeing up resources for other aspects of your disaster recovery strategy. The sooner you recover your data, the better and the faster the cloud backup.

Final Thoughts

Cloud backup solutions can help you in long term. It can be your perfect partner in fulfilling your vision. Get the best cloud backup solutions from the leading cloud backup service provider Datanet. For more information visit https://www.datanethosting.com/

[cutest-stuff]

Datanet Hosting provides online backup services to cloud for PCs, Macs, iPhones, Android and other mobile devices all into one account for one low fee. cloud backup storage is a service in which the data and applications on a group's servers are backed up and stored on a remote server. We are offering 1-month free trial of backup on cloud and assuring the lowest price guarantee. 

[rapidit]

Norton 360 Deluxe’s software boasts a powerful firewall, VPN with no limitations, cross-platform security, and a hosted online backup filled to the brim with high-security features. Its interface is familiar, and easy to use, with panels linked to security, online safety, backup, and performance, and lab test results that prove persistent threats will be rooted out and destroyed in no time.

[backupgurublog]

Data always plays a very important role in this corporate world. Though you take many steps to protect your data, you are still at risk.

[casperlawrence]

What Types of Services Can be Provided by Web Servers Hosting?

If you’re creating a website, you’ll need to select a web host to supply the computing power and make the website available to global audiences. In this article, we’ll explain what web servers hosting is and the services you should anticipate from a dependable web host.

When you’re attempting to create a website, you may have heard of “web hosting” or a “web host”. But what is a web host? And why is web hosting so crucial when creating a website? Primarily, a web host provides the computing power necessary to power your website’s code and give its data to visitors.

Nevertheless, it’s not always that easy, because some web hosts offer more than just the basics to make things easier for you and help your website excel.

In this article, we’ll go over all the information you need to know about the fundamentals of web hosting. We’ll look at what a web host is, why it’s necessary, and the types of services you can expect from a dependable web host. Let’s get started.

What Is a Web Host?

A web host is a type of service provider that allows organizations and individuals to make their websites accessible via the World Wide Web. They provide the necessary hardware, software, storage, and internet access to enable the websites to be viewed on the internet.

What Should Web Hosts Provide?

Storage: A web host provides the physical space on a server where files and data related to a website are stored.

Domain Name: A web host can also provide a domain name, which is the address of a website.

Website Building Tools: Some web hosts provide website-building tools that make it easier to design and build websites.

Email Services: Web hosts can also provide email services, allowing users to create and manage email accounts associated with their websites.

Security: Web hosts can offer security features such as firewalls and encryption to protect websites from malicious attacks.

Support: Web hosts can provide technical support to help customers with any issues they may have.

5 Different Types of Web Hosting

Dedicated hosting: Dedicated hosting provides a single user with exclusive access to a physical server. This is the most powerful and expensive hosting option available.

Cloud hosting: Cloud hosting is a type of web hosting that uses multiple servers connected to a cloud computing platform to provide scalability, flexibility, and reliability.

Shared hosting: Shared hosting is the most common and cost-effective type of web hosting. It allows multiple websites to be hosted on a single server, with resources shared between them.

Virtual Private Servers (VPS): A VPS is a virtual machine that runs its own copy of an operating system and provides users with root access. It is a more powerful and flexible option than shared hosting, but still less costly than dedicated hosting.

Colocation Services: Colocation services are provided by data centers that offer physical space for hosting servers. They provide space, power, cooling, and physical security for the servers.

Conclusion

A web host provides the storage, bandwidth, and other services that are necessary for a website to be accessible to visitors through the World Wide Web. These services include domain registration, web hosting, website building, and server maintenance. Additionally, server hosting companies may provide additional services such as email hosting, search engine optimization, and customer support.

[freshpc-computer-service-hu-blog]

Wist je dat er minder wordt ingebroken als je een camera als beveiliging hebt hangen?

De aanwezigheid van camerasystemen zullen inbrekers en vandalen doen afschrikken vanwege de verhoogde herken en pakkans. Zo blijven waardevolle eigendommen of bedrijfspanden buiten het bereik van ongewenste individuen.

Hoe staat het ervoor met de beveiliging van jouw woning of bedrijfspand? Neem snel contact op om de mogelijkheden te bespreken.

FreshPC Computer Service Huissen ☎️06 3451 5782

[supramsinfo]

How to Backup and Recover Deleted Data with Acronis Backup Solutions?

Get Acronis Backup!

Often we can’t find a file deleted on our computer, mobile gadget, USB drive, or tablet, in places where we could be hoping they would be.

Does it mean in case it’s nowhere to be found and you don’t have a backup, is it gone forever?

Not unavoidably because with the right tool, you can restore your precious data.

With Acronis Backup Solutions, you can make your digital life better.

When you back up your device with Acronis True Image from Acronis, you can back up your entire data. This covers many editions of a specific file.

With just a simple search and restore you can rapidly and easily recover the most recent edition of a deleted file.

Moving on to the question-- How to Backup and Recover Deleted Data with Acronis Backup Solutions--follow this 4-step process!

Start Acronis True Image 2020.

On the sidebar, press the ‘Backup’ button.

From the backup list, select the backup with the concerned file.

Finally, on the right panel, press ‘Recover files’ button.

How does Acronis backup work?

Acronis Backup Solutions provide you with many good options to keep you data safe and protected from accidental happenings, such as the removal of a precious file unknowingly.

The Backup operation of the highly effective and powerful Acronis software generates an image file for the objects of backup and disaster recovery. On the other hand, the Disk Clone tool just copies/moves the whole contents of one hard disk drive to a different one. You may save this image to any supported storage gadget, and utilize the same as a backup or for the objects of disaster recovery.

Get In Touch

Web: https://www.suprams.com/

Phone: +1-800-786-0281(USA) | +91-955-549-9125(IND)

Address: Office Address:- 817-A, 8th Floor,  Jaina tower 2, District Center, Janakpuri, New Delhi, 110058.

[docquickdms]

Security Concerns Solved by #Docquik

Enable access to only the users you want. With our advanced audit trail, track activities involving your files. Thanks to our #cloud backup, our #onlinebackup and recovery plan lets you obtain all your backed-up data without loss.

[mega-okesipe-victoria-o]

R code for churn prediction-OKESIPE VICTORIA (Final Year Project 2019)

_______Title:

PREDICTING CUSTOMER CHURN IN MOBILE TELECOMMUNICATION SECTOR USING DATA MINING ANALYSIS APPROACH WITH R

________

```{r} library(plyr) library(corrplot) library(ggplot2) library(gridExtra) library(ggthemes) library(caret) library(MASS) library(randomForest) library(party) ``` ```{r} churn <- read.csv('Telco-Customer-Churn.csv') str(churn) ``` The raw data contains 7043 rows (customers) and 21 columns (features). The “Churn” column is our target. We’ll use all other columns as features to our model. We use sapply to check the number if missing values in each columns. We found that there are 11 missing values in "TotalCharges" columns. So, let's remove these rows with missing values. ```{r} sapply(churn, function(x) sum(is.na(x))) ``` ```{r} churn <- churn[complete.cases(churn), ] ``` Change “No internet service” to “No” for six columns, they are: “OnlineSecurity”, “OnlineBackup”, “DeviceProtection”, “TechSupport”, “streamingTV”, “streamingMovies”. ```{r} cols_recode1 <- c(10:15) for(i in 1:ncol(churn[,cols_recode1])) {        churn[,cols_recode1][,i] <- as.factor(mapvalues                                              (churn[,cols_recode1][,i], from =c("No internet service"),to=c("No"))) } ``` Change “No phone service” to “No” for column “MultipleLines” ```{r} churn$MultipleLines <- as.factor(mapvalues(churn$MultipleLines,                                           from=c("No phone service"),                                           to=c("No"))) ``` The minimum tenure is 1 month and maximum tenure is 72 months, we can group them into five tenure groups: “0–12 Month”, “12–24 Month”, “24–48 Months”, “48–60 Month”, “> 60 Month”. ```{r} min(churn$tenure); max(churn$tenure) ``` ```{r} group_tenure <- function(tenure){    if (tenure >= 0 & tenure <= 12){        return('0-12 Month')    }else if(tenure > 12 & tenure <= 24){        return('12-24 Month')    }else if (tenure > 24 & tenure <= 48){        return('24-48 Month')    }else if (tenure > 48 & tenure <=60){        return('48-60 Month')    }else if (tenure > 60){        return('> 60 Month')    } } ``` ```{r} churn$tenure_group <- sapply(churn$tenure,group_tenure) churn$tenure_group <- as.factor(churn$tenure_group) ``` Change the values in column “SeniorCitizen” from 0 or 1 to “No” or “Yes”. ```{r} churn$SeniorCitizen <- as.factor(mapvalues(churn$SeniorCitizen,                                      from=c("0","1"),                                      to=c("No", "Yes"))) ``` Remove the columns we do not need for the analysis: ```{r} churn$customerID <- NULL churn$tenure <- NULL ``` ##Exploratory data analysis and feature selection ```{r} numeric.var <- sapply(churn, is.numeric) ## Find numerical variables corr.matrix <- cor(churn[,numeric.var])  ## Calculate the correlation matrix corrplot(corr.matrix, main="\n\nCorrelation Plot for Numeric Variables", method="number") ``` The Monthly Charges and Total Charges are correlated. So one of them will be removed from the model. We remove Total Charges. ```{r} churn$TotalCharges <- NULL ``` ## Bar plots of categorical variables ```{r} p1 <- ggplot(churn, aes(x=gender)) + ggtitle("Gender") + xlab("Gender") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p2 <- ggplot(churn, aes(x=SeniorCitizen)) + ggtitle("Senior Citizen") + xlab("Senior Citizen") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p3 <- ggplot(churn, aes(x=Partner)) + ggtitle("Partner") + xlab("Partner") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p4 <- ggplot(churn, aes(x=Dependents)) + ggtitle("Dependents") + xlab("Dependents") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() grid.arrange(p1, p2, p3, p4, ncol=2) ``` ```{r} p5 <- ggplot(churn, aes(x=PhoneService)) + ggtitle("Phone Service") + xlab("Phone Service") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p6 <- ggplot(churn, aes(x=MultipleLines)) + ggtitle("Multiple Lines") + xlab("Multiple Lines") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p7 <- ggplot(churn, aes(x=InternetService)) + ggtitle("Internet Service") + xlab("Internet Service") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p8 <- ggplot(churn, aes(x=OnlineSecurity)) + ggtitle("Online Security") + xlab("Online Security") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() grid.arrange(p5, p6, p7, p8, ncol=2) ``` ```{r} p9 <- ggplot(churn, aes(x=OnlineBackup)) + ggtitle("Online Backup") + xlab("Online Backup") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p10 <- ggplot(churn, aes(x=DeviceProtection)) + ggtitle("Device Protection") + xlab("Device Protection") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p11 <- ggplot(churn, aes(x=TechSupport)) + ggtitle("Tech Support") + xlab("Tech Support") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p12 <- ggplot(churn, aes(x=StreamingTV)) + ggtitle("Streaming TV") + xlab("Streaming TV") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() grid.arrange(p9, p10, p11, p12, ncol=2) ``` ```{r} p13 <- ggplot(churn, aes(x=StreamingMovies)) + ggtitle("Streaming Movies") + xlab("Streaming Movies") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p14 <- ggplot(churn, aes(x=Contract)) + ggtitle("Contract") + xlab("Contract") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p15 <- ggplot(churn, aes(x=PaperlessBilling)) + ggtitle("Paperless Billing") + xlab("Paperless Billing") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p16 <- ggplot(churn, aes(x=PaymentMethod)) + ggtitle("Payment Method") + xlab("Payment Method") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() p17 <- ggplot(churn, aes(x=tenure_group)) + ggtitle("Tenure Group") + xlab("Tenure Group") +  geom_bar(aes(y = 100*(..count..)/sum(..count..)), width = 0.5) + ylab("Percentage") + coord_flip() + theme_minimal() grid.arrange(p13, p14, p15, p16, p17, ncol=2) ``` All categorical variables have a reasonable broad distribution, therefore, all of them will be kept for the further analysis. ## Logistic Regression Model Fitting Split the data into training and testing sets. ```{r} intrain<- createDataPartition(churn$Churn,p=0.7,list=FALSE) set.seed(2019) training<- churn[intrain,] testing<- churn[-intrain,] ``` Confirm the splitting is correct. ```{r} dim(training); dim(testing) ``` Fitting the Model ```{r} LogModel <- glm(Churn ~ .,family=binomial(link="logit"),data=training) print(summary(LogModel)) ``` Feature analysis: 1. The top three most-relevant features include Contract, Paperless Billing and tenure group, all of which are categorical variables. ```{r} anova(LogModel, test="Chisq") ``` Analyzing the deviance table we can see the drop in deviance when adding each variable one at a time. Adding InternetService, Contract and tenure_group significantly reduces the residual deviance. The other variables such as PaymentMethod and Dependents seem to improve the model less even though they all have low p-values. ## Assessing the predictive ability of the model ```{r} testing$Churn <- as.character(testing$Churn) testing$Churn[testing$Churn=="No"] <- "0" testing$Churn[testing$Churn=="Yes"] <- "1" fitted.results <- predict(LogModel,newdata=testing,type='response') fitted.results <- ifelse(fitted.results > 0.5,1,0) misClasificError <- mean(fitted.results != testing$Churn) print(paste('Logistic Regression Accuracy',1-misClasificError)) ``` ## Confusion Matrix ```{r} print("Confusion Matrix for Logistic Regression"); table(testing$Churn, fitted.results > 0.5) ``` ## Odds Ratio One of the interesting perfomance measurements in logistic regression is Odds Ratio.Basically, Odds retios is what the odds of an event is happening? ```{r} exp(cbind(OR=coef(LogModel), confint(LogModel))) ``` For each unit increase in Monthly Charge, there is a 2.4% decrease in the likelihood of a customer's churning. ## Decision Tree ```{r} churn <- read.csv('Telco-Customer-Churn.csv') churn <- churn[complete.cases(churn), ] ``` ```{r} cols_recode1 <- c(10:15) for(i in 1:ncol(churn[,cols_recode1])) {        churn[,cols_recode1][,i] <- as.factor(mapvalues                                              (churn[,cols_recode1][,i], from =c("No internet service"),to=c("No"))) } ``` ```{r} churn$MultipleLines <- as.factor(mapvalues(churn$MultipleLines,                                           from=c("No phone service"),                                           to=c("No"))) ``` ```{r} group_tenure <- function(tenure){    if (tenure >= 0 & tenure <= 12){        return('0-12 Month')    }else if(tenure > 12 & tenure <= 24){        return('12-24 Month')    }else if (tenure > 24 & tenure <= 48){        return('24-48 Month')    }else if (tenure > 48 & tenure <=60){        return('48-60 Month')    }else if (tenure > 60){        return('> 60 Month')    } } ``` ```{r} churn$tenure_group <- sapply(churn$tenure,group_tenure) churn$tenure_group <- as.factor(churn$tenure_group) ``` ```{r} churn$SeniorCitizen <- as.factor(mapvalues(churn$SeniorCitizen,                                      from=c("0","1"),                                      to=c("No", "Yes"))) ``` ```{r} churn$customerID <- NULL churn$tenure <- NULL churn$TotalCharges <- NULL ``` ```{r} intrain<- createDataPartition(churn$Churn,p=0.7,list=FALSE) set.seed(2019) training<- churn[intrain,] testing<- churn[-intrain,] ``` For illustration purpose, we are going to use only three variables, they are "Contract", "tenure_group" and "PaperlessBilling". ```{r} tree <- ctree(Churn~Contract+tenure_group+PaperlessBilling, training) ``` ```{r} plot(tree, type='simple') ``` Out of three variables we use, Contract is the most important variable to predict customer churn or not churn. If a customer in a one-year contract and not using PapelessBilling, then this customer is unlikely to churn. On the other hand, if a customer is in a month-to-month contract, and in the tenure group of 0-12 months, and using PaperlessBilling, then this customer is more likely to churn. ```{r} pred_tree <- predict(tree, testing) print("Confusion Matrix for Decision Tree"); table(Predicted = pred_tree, Actual = testing$Churn) ``` ```{r} p1 <- predict(tree, training) tab1 <- table(Predicted = p1, Actual = training$Churn) tab2 <- table(Predicted = pred_tree, Actual = testing$Churn) ``` ```{r} print(paste('Decision Tree Accuracy',sum(diag(tab2))/sum(tab2))) ``` ______________________________ end of R code for churn prediction

[smaccloud]

Easily #access your #files, #Photos, #Videos etc. from #Anywhere around the #World. Visit https://www.smaccloud.com/features/ #FileSharing #OnlineDataStorage #OnlineStoring #onlinebackup #cloudstorage #business #cloudsharing #cloudserver #free #cloudhosting #SMACCloud #cloudbackup #home #personal #storageapp #photostorage

[evrrrrrrrr]

Cloud Backup keeps data secure and certifies business continuity by keeping devices with an automated backup process that is easy to use and manage. Datanet offered cloud backup solutions at the affordable cost.