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Scala Vs Python - Choosing the best language for Apache Spark

Apache Spark is a high-speed cluster computing technology, that accelerates the Hadoop computational software process and was introduced by Apache Software Foundation. Apache Spark enhances the speed and supports multiple programming languages such as - Scala, Python, Java and R. All these 4 APIs possess their own special features and are predominant for programming in Spark. But data scientists usually prefer to learn Python and Scala for Spark, as Java does not support Read-Evaluate-Print-Loop, and R is not a general purpose language. Both Python and Scala are easy to program and help data experts get productive fast. Choosing a programming language for Apache Spark depends on the type of application to be developed. Scala vs Python for Spark Both are Object Oriented plus functional and have the same syntax and passionate support communities. Below a list of Scala Python comparison helps you choose the best programming language based on your requirements. Scala vs Python Performance Scala is a trending programming language in Big Data. It runs 10 times faster than Python, as it uses Java Virtual Machine in runtime. Python is highly productive and a very simple language to learn. Whereas, Scala, due to its high-level functional features requires more thinking and abstraction. But once you get familiar with Scala, your productivity will dramatically boost. Both are good in their specifications, but if you are working with simple intuitive logic then Python does the job greatly. And if you are developing something more complex, then go for Scala. Refactoring the Code Safely There is a need to refactor the code continuously when programming with Apache Spark. Scala is a statically typed language and Python is a dynamically typed language. Refactoring the program code of a statically typed language is much easier and hassle-free than refactoring the code of dynamic language. Many a time, developers face difficulties after modifying the program code of python. This is because it creates more bugs than fixing the older ones. So, it is better to choose Scala which is a compiled language. Scala, Python Integration The diverse and complex infrastructure of Big Data systems requests a programming language, that has the power to integrate across several services and databases. Scala, with the Play framework, has the ability to integrate easily with various concurrency primitives like Akka’s actors in the Big Data ecosystem, as it offers many reactive cores and asynchronous libraries. Scala allows developers to write maintainable, readable and efficient services. Python, using uWSGI, supports heavyweight process forking but does not support true multithreading. User-friendly Language Both Python and Scala are equally powerful languages in the context of Spark. So the desired functionality can be achieved either by using Python or Scala. But when compared to Scala, Python is very easy to understand. Python is less prolix, that helps developers to write code easily in Python for Spark. Scala vs Python for Machine Learning Python language is recommended if you are implementing Machine Learning algorithms like Graphx or GraphFrames or MLlib and data science technologies. MLlib only contains parallel Machine Learning algorithms, that are appropriate to run on a bunch of distributed data set. Developers with a good command over Python can build ML application without SPARK MLLIB. But if you are designing ML models, then Scala is the best choice because any new addition of ML algorithms will be implemented first in Scala and then Python. Scala is preferred for implementing data engineering technologies. Conclusion Python is slower but very easy to use, while Scala is fastest and moderately easy to use. Scala provides access to the latest features of the Spark, as Apache Spark is written in Scala. Language choice for programming in Apache Spark depends on the features that best fit the project needs, as each one has its own pros and cons. So, it is necessary for developers to learn both Scala and Python before choosing a programming language. Also Read: 7 Useful Machine Learning Packages in R  
Scala Vs Python - Choosing the best language for Apache Spark 89 Scala Vs Python - Choosing the best language for Apache Spark Blog
Susan May 19 Sep 2017
Apache Spark is a high-speed cluster computing technology, that accelerates the Hadoop computational software process and was introduced by Apache Software Foundation. Apache Spark enhances the speed ...
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Microsoft penetrating Cryptocurrency Market with the Blockchain technology

Microsoft corporation has chosen to enter the crypto currency market with the blockchain technology. The company is apparently collaborating with Israel's Bank Hapoalim, the first bank that uses blockchain technology for digital bank contracts. Bank contract means giving assurance from a particular bank, that borrower's indebtedness will be met even if their liability is not attained. Blending the blockchain with bank contract is the thing that happened for the first time in the history of Israel’s banking sector. Applicants do not need to visit the bank, once the application is installed and the documentation process will be highly secured and will consume less time. According to the MarketsandMarkets report, by the end of 2021, the blockchain market is expected to reach $2.31 billion from $210.2 million in 2016, at a CAGR (compound annual growth rate) of 61.5%. Since the initiation of the cryptocurrency transactions, blockchain technology has been put to practice. The technology is now more popular because of the fact that it cannot be ruptured and offers high security. Microsoft has garnered the faith of a huge number of blockchain customers, and its recent collaboration with Hapoalim bank in Israel is expected to elevate the company’s growth in the near future. Source: Microsoft Official Blog  
Microsoft penetrating Cryptocurrency Market with the Blockchain technology

Microsoft penetrating Cryptocurrency Market with the Blockchain technology

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Microsoft corporation has chosen to enter the crypto currency market with the blockchain technology. The company is apparently collaborating with Israel's Bank Hapoalim, the first bank that uses b...
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Google Safe Browsing Service now protecting more than 3 billion devices

Google has recently released a new statistics related to its Safe Browsing Service. The search giant announced that now more than 3 billion desktops or mobile devices running on Chrome, Safari, and Firefox are being protected from visiting potentially dangerous sites with this new Safe Browsing service. Additionally, many web app developers including Snapchat are using this service to protect their users. The Safe Browsing service was launched in 2007, and it was one of Google’s earliest anti-malware efforts. In the year 2016, Google released a figure of 2 million and this was the number of devices being protected by Safe Browsing service. As per a blog post by Google, “This notification is one of the visible parts of Safe Browsing, a collection of Google technologies that hunt badness—typically websites that deceive users—on the internet.” For many years, Google has been using machine learning in Safe Browsing. This has helped them in detecting much web-based malware and removing them. Google also included, “We’re continually evaluating and integrating cutting-edge new approaches to improve Safe Browsing”.  
Google Safe Browsing Service now protecting more than 3 billion devices

Google Safe Browsing Service now protecting more than 3 billion devices

What's New
Google has recently released a new statistics related to its Safe Browsing Service. The search giant announced that now more than 3 billion desktops or mobile devices running on Chrome, Safari, and Fi...
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7 Useful Machine Learning packages in R

Choosing a programming language for machine learning depends on the specifications of a given task and the environment where the ML activities are to be performed. Kaggler’s Favourite Tools survey says that out of 1714 Kaggler’s, 543 are preferring the open source programming language R. R is the best choice for data experts who want to understand and prospect the data, using graphs and statistical methods. It has various advanced implementations and ML packages for the top ML algorithms, that are essential to know for every data scientist to design and explore the given data. The Black Box in R is known as Package, which is a collection of pre-written codes that can be used whenever required. According to CRAN (Comprehensive R Archive Network), approximately 8,341 packages are available today. The users can install these ML packages simply by using the syntax i.e install.packages (“Name_Of_R_Package”). List of a few R packages used for Machine Learning is given below:- RODBC implements ODBC RODBC is the perfect package to choose if you want to convert the data stored in Open Database Connectivity or SQL databases into R data frame. library(RODBC) can be used to load the RODBC function and install.packages(“RODBC”) to install the RODBC package. Wordcloud Package in R Wordcloud allows you to create a graphical picture of words and you can arrange the words in a unsystematic fashion, place the most frequently used words close together in the center, identify the frequency of a specific word etc., resulting in a long lasting impression. It can be loaded with library(wordcloud) and installed using install.packages(“wordcloud”). CARET analyses the best algorithm CARET is one of the leading packages in R language. It is always a question that which is the best algorithm for a given task. This package gives the best results in finding the best algorithm and allows data scientists to run various algorithms for business problems. e1071 helps to find the conditional probability Conditional probability is essential for some forms of analyses, for example: to find the probability that a person who buys a cup also buys a saucer. This can be done with the help of e1071 package. This package of R language also provides naiveBayes( ) function based on conditional probability. Kernlab Package Machine Learning Image processing is one of the difficult tasks, which Support Vector Machine (SVM) eases to a great extent. The implementation of SVM is possible easily with Kernlab package and SVM has several Kernel functions such as laplacedot, polydot, tanhdot and much more. SVM is not at all possible and completely functional without the Kernel functions. RStudio Shiny Package The open source R package i.e Shiny allows beautiful and well-built web frameworks for developing web applications using R. Without the need of any knowledge of HTML, CSS, and JavaScript, it allows you to build interactive web applications. Lubridate Package Machine Learning The techniques used with date-times must be powerful. But in some situations, R language fails to achieve it. According to package authors, the Lubridate package has the same and catchy syntax that makes working with dates and times easy, by providing tools. Conclusion Different machine learning packages are available in the Comprehensive R Archive Network repository. All these packages are used to design efficient models, but make sure that you understand the specifications clearly before applying an algorithm. Because a small change in the parameter can change the output completely.  
7 Useful Machine Learning packages in R

7 Useful Machine Learning packages in R

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Choosing a programming language for machine learning depends on the specifications of a given task and the environment where the ML activities are to be performed. Kaggler’s Favourite Tools surv...
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7 Advantages of Developing Apps with MEAN Stack

Various technologies are developed to provide services for increasing demand of mobile and web applications across the globe. Among all, MEAN which is a free and open-source JavaScript software stack holds a great importance for developing dynamic web applications and websites. The acronym MEAN stands for the MongoDB, ExpressJS, AngularJS, and Node.js, which are open source JavaScript based technologies. A full-stack JavaScript framework which is used to develop web apps quickly and easily can be enabled by using all these powerhouse technologies together. Let us discuss some of the advantages of MEAN stack for which developers are choosing it for developing mobile apps and websites. MEAN makes the switching between client and server easier Developing apps using MEAN is simple and fast because developers are allowed to write code only in one language i.e JavaScript for both client and server side. A JavaScript specialist can manage the complete project with the help of MEAN Stack formula. With Node.js, a developer can deploy the applications on the server directly without the need of deploying it to a stand-alone server. Isomorphic Coding is possible with MEAN Transferring the code to another framework that is written in one particular framework is made easier with the help of MEAN stack. This made MEAN stack a leading edge technology and the MEAN stack development companies are considering plenty of technologies in MEAN to boost the transcendence in applications and web development projects. Highly Flexible MEAN allows you to test an application on cloud platform easily after successful completion of a development process. Applications can be easily developed, tested and introduced in the cloud. It also allows you to add extra information simply by adding the field to your form. MongoDB, specifically designed for the cloud, provides full cluster support and automatic replication. MEAN uses JSON JSON (JavaScript Object Notation) is used in both NodeJS and AngularJS. And MongoDB is a component based relational database that offers users to save documents in JSON format. But it is limited for only small to intermediate level companies. Mostly, developers prefer MEAN stack at various stages of applications and web development. Cost effective Developing apps with MEAN stack requires developers who are proficient at JavaScript, whereas LAMP stack requires developers who are expert in MySQL, JavaScript, and PHP. As less number of developers are required to develop apps using MEAN stack, the amount to be invested to hire the number of developers will also be less. So, we can say MEAN stack is highly cost effective and often, the most effective way of dealing with. High Speed and Reusability Node.js is speedy and ascendable because of its non-blocking architecture. Angular.js is an open source JavaScript framework that offers maintenance, testability, and reusability. Powerful directives of this framework progress into great testability and domain specific language. Open Source and Cloud Compatible All the MEAN stack technologies are open source and available for free. It helps the development process using libraries and public repositories and reduces the development cost. MongoDB helps to deploy cloud functionalities within the app by reducing the disk space cost. Conclusion MEAN stack is fast developing, easy to learn and easy to combine around. Any technology available in Stack can be used easily in integration with another, depending on the requirement. However, it is definitely a new cutting edge technology and innovation that will possibly rule the market shortly. Also Read:  MEAN Stack - Evolution Of Web Development
7 Advantages of Developing Apps with MEAN Stack

7 Advantages of Developing Apps with MEAN Stack

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Various technologies are developed to provide services for increasing demand of mobile and web applications across the globe. Among all, MEAN which is a free and open-source JavaScript software stack ...
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How AI is dominating the Field of Marketing: Five Real-Time Observations

Artificial Intelligence platform of IBM, Watson is loquacious: it tells jokes, answers the questions and write songs as well. AI platform of Google can read lips better than a professional does, and it is capable enough to master video games within a short period. It can predict actions on video two seconds before it begins with MIT’s AI. Tesla has another AI platform which successfully powering the company to introduce self-driving cars. All these things are propelling us closer to the world of machines which are more intelligent than humans. Automation and artificial intelligence are profoundly transforming the trade and commerce industry. Scientists, marketers, and futurists agree to the notion that the emergence of Artificial Intelligence and Automation will have a significant impact on society. It is predicted that Artificial Intelligence will bring a complete and spontaneous change in society with more utopian outcomes. Artificial Intelligence in Marketing Field Artificial intelligence is a hot topic in marketing. It is considered as the next frontier of marketing. AI is a broad term which has covered a wide range of different technologies. The concept of AI refers to technology that is seeking to mimic human intelligence. AI includes a broad variety of capabilities such as voice, image recognition, machine learning and semantic searching. Marketers like to wax lyrical about new and exciting updated technologies. They rely on AI for image recognition and speech recognition. It also prevents data leaks in marketing and helps in targeting drones at remote communities. Marketers believe that AI will accelerate sales and marketing. In the next few years, it is expected that we are going to have autonomous, self-driving marketing automation. Machine learning will improve sales as well as marketing software and allow this software to do things without any explicit instructions. Be it predictive lead scoring, content recommendations or e-mail acquisitions, machine learning has improved all the things. AI Transforming Markets Traditional marketing or outbound marketing campaigns are far less efficient in winning and retaining a customer than once they were. AI is important to gain sustainable competitive advantage in this always connected, real world where marketers are required to deliver continuous, customized, insight driven interactions with customers on an individual basis. Brands that have understood the significance of AI and put the right system in place to scale are successful in creating a competitive advantage which is very difficult to replicate. This is because artificial intelligence is not about technology, it is about delivering the perfect combination of content with context. Big data begets big complexities and machines are better equipped to unravel the enormous complexities in case of big data. The introduction of new and more sophisticated technologies are increasing the gap between strategy and system. Marketers and leaders are seeking alternatives to close this gap. Moreover, demand for customized conversions and personalized experiences is accelerating. Which means, marketers are required to have a right system in place to deliver personalized experiences to customers. AI also has made it possible for brands to manage the execution of in-house data because it is as valuable as the brand itself. Marketers are using innovative AI based systems to execute strategies to deliver revenue growth and cost reductions. It is also mitigating the risk of damaging customer relationships. Also Read: Artificial Intelligence Impact on Content Marketing AI implication in Inbound Marketing AI applications have a significant impact in marketing. Different applications are known for playing different roles across the customer journey. Some are known for attracting customers while other are used for conversions and re-engaging past customers. You can divide these applications and their implications concerning RACE framework. Image Source: smartinsights.com How AI is dominating the Field of Marketing: Five Real Time Observations     AI, particularly machine learning is an integral part of marketing. Here is the list of five real-world examples which can help you understand how AI and machine learning is dominating the field of marketing. IBM Watson IBM Watson is a cognitive system or a strategic partnership between system and people. Having Watson means you have an AI platform for businesses which can help you uncover insights, engage with the customer in new ways and make decisions with more confidence. IBM Watson allows you to build Chatbot and virtual agents that answer customer queries and help marketers respond to their needs quickly and efficiently. Watson is working with people in 45 countries and 20 industries. It is helping people to work faster and work smarter than ever before. IBM Watson is successfully transforming customer experiences with bots. Chatbots let users interact with their organizations in real time. They speak to us, answer questions and offer support within seconds. It also allows you to add a natural language interface to the app, website or device. These bots help in breaking down the barriers in fast and efficient customer communications. AI Platform of Tesla MIT ranks Tesla second in the list of World's 13 Smartest Artificial Intelligence Companies. This electric auto manufacturing company is taking advantage of machine learning technology to collect data from all of its cars on the road. The company then utilizes such data to build a better performance into its Autopilot features. Autopilot features, the results of AI technology are successful in reducing accidents by 50%.  The company makes the use of radar as a primary control sensor, camera, and additional technology as a supplement. However, AI technology is helping the car to understand the object more clearly in its way. MIT     MIT has published a paper on new artificial intelligence platform which is known as AI2. This platform makes the use of human input combined with machine learning to reduce false positives and to increase its ability to predict the cyber-attacks. Cybersecurity professionals are facing daunting tasks. They are required to protect enterprise networks from threats and limit the damages when data breaches occur. Cybersecurity is a challenge in industries where the companies are short-staffed, and they are unable to find trained staffs. In such cases, the AI2 platform can help businesses ensure cyber security. The AI2 platform is capable enough to predict cyber-attacks with 85% rate of accuracy. Uber Uber is not only a company that merely schedules rides but is also considered as a software and technology company which heavily relies on machine learning and artificial intelligence. The amount data which the company is required to handle is huge and machine learning helps executives to use that data for business value. Uber is not extremely open about the use of technology, but it helps with logistics and many other aspects of the business. Uber is continuously expanding the use of machine learning by investing in autonomous vehicles. Uber makes use of machine learning and artificial intelligence platforms to figure out ways to retain their customers and to increase customer value.   Salesforce Salesforce is the largest tech company on the list. AI has introduced Einstein platform in 2016, which is customizable for customers and make the use of machine learning, deep learning, predictive analytics, natural language processing and smart data discovery. This AI platform has introduced the larger trend among tech providers which are using AI and machine-learning technology to improve their own businesses. 451 Research’s Patience said that Salesforce is making the use of customer data including emails and collect activity data from tools such as Chatter and external sources like social media. It also makes use of signals from IoT devices and uses them to train machine learning models to drive features within the applications. Artificial intelligence is a new trend which is bringing a storm to the world of marketing. Many marketers are still in the dark. They don’t know how to leverage AI strategies in everyday marketing campaigns. AI-driven marketing solutions sound like future of marketing, but some creative minds are here to take over the most tedious and time-consuming tasks that marketers are struggling to deal with. Above mentioned real-world examples of AI suggest that it is offering marketers an unprecedented ability to improve personalization, productivity, and performance. Final Thoughts     “Everything we love about civilization is a product of intelligence, so amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never before – as long as we manage to keep the technology beneficial.” (Max Tegmark, President of the Future of Life Institute) We have only scratched the surface of Marketing to collect real-world examples of AI and machine learning technology; there is a lot more to find out! From Siri to self-driving cars, from Google’s search algorithms to IBM’s Watson to autonomous weapons, AI is a part and parcel of nearly every field. Artificial intelligence and machine learning are useful for all functions of a business. Marketing is also not an exception. AI has a significant impact on marketing, and it is going to shape further, the future of marketing and a way to forge the relationship between companies and clients.  
How AI is dominating the Field of Marketing: Five Real-Time Observations

How AI is dominating the Field of Marketing: Five Real-Time Observations

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Artificial Intelligence platform of IBM, Watson is loquacious: it tells jokes, answers the questions and write songs as well. AI platform of Google can read lips better than a professional does, and i...
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Artificial Intelligence News Engine Lands on Opera Mini for iPhone users in India

On Tuesday, Opera has launched a new version of its well-known mobile browser app, Opera Mini in India for iPhone and iPad users. The new version uses Artificial Intelligence that provides news 4 times faster than the previous version. Not only in English, this news feed is also available in Hindi, Tamil, and Gujarati. Opera’s Artificial Intelligence uses real-time intelligence ranking, powered by deep learning and machine learning to find out users’ likes and dislikes and offer them news that they can connect with more in the “For You” section. The new version app allows users to choose the news location wise and sections as per their choice. "The goal is to provide each user the ability to get their optimal content based on their interest, which is constantly evolving," said Cuautemoc Weber, Head of Global Accounts and Content, Opera Software. "This is also applied to bringing new information which perhaps the user would not have been able to gather from their traditional sources," Weber added. The company designed the app to make it look more appealing, by changing the search and address bar color to red. It now brings forth that it is no more an ordinary address bar, but it also scans your QR (Quick Response) codes and allows you to customize your search engine. This new feature is now available only in few countries such as South Africa, United States, Indonesia, Ghana, India, Nigeria, Kenya, and Tanzania. The company is now planning to extend its services to Pakistan, Bangladesh, and Russia.   Source: Opera Official Blog  
Artificial Intelligence News Engine Lands on Opera Mini for iPhone users in India

Artificial Intelligence News Engine Lands on Opera Mini for iPhone users in India

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On Tuesday, Opera has launched a new version of its well-known mobile browser app, Opera Mini in India for iPhone and iPad users. The new version uses Artificial Intelligence that provides news 4 time...
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5 Reasons to use Xamarin for cross-platform application development

The mobile development market is growing at an exceptional rate due to huge consumer mobility and is divided among iOS, Android, Windows and other mobile operating systems. According to IBM research, 75% of mobile development projects fail mainly because of three reasons- project objectives, schedule, and budget. Xamarin's cross-platform application development that was acquired by Microsoft is a great answer to these challenges. Gartner says, “By 2017, mobile apps will be downloaded more than 268 billion times, generating revenue of more than $77 billion and making apps one of the most popular computing tools for users across the globe.” Cross-platform mobile development has become significant for modern businesses, as the global market share of mobile platforms is changing at regular intervals. Cross-platform mobile apps can be built in a faster and more cost-efficient way when compared to native mobile apps. Xamarin using C# helps to develop mobile apps easily that operates across multiple platforms. Here we present 5 reasons why Xamarin is the best for cross-platform development. Easy to learn To develop Android and iOS apps, it normally requires two separate programming languages, that is, Java and Objective-C respectively, which requires you to understand two different ways of doing the same thing. Whereas, using Xamarin you need to learn only one language i.e C#, which helps to develop apps across multiple mobile operating systems. So, it is easy to learn a single language rather than two different languages for the same process. Offers native user experience The popular and preferred solution for any mobile application development is native design. This is where Xamarin comes in, which provides native look and feel to an application. It offers native API, native UI and native performance which Android, iOS, and Windows phone apps use when developed on their platform. Sharing code base among the platforms is easy to accomplish with Xamarin, helping you shorten the development cycle. The shared code base, as well as its libraries with Xamarin cross platform visual studio empowers writing single software for all OS. At the same time, this software offers completely native user experience, behavior and appearance patterns. Xamarin Test Cloud Testing plays a key role in software development. Xamarin Test Cloud is a platform which gives access to test an application on multiple real devices in the cloud.  It provides the tools and libraries to create automated tests and confirm that the behavior is perfect. This helps to make sure that the application performs efficiently and correctly across different devices with less effort. Xamarin has brought a new feature called Xamarin Test Recorder, which helps a lot in the testing implementation by recording the device touches and transforming them into code. Simplified Development and Maintenance Since cross-platform app development abolishes the need for separate apps for different mobile OS, Xamarin also enjoys this benefit and makes maintenance and updates easier. Any changes or updates made to the source file will be applied to all apps that use Xamarin.Forms. This reduces the workforce required to develop apps that function on all existing mobile platforms and also a single team can be able to troubleshoot app performance obstacles after deployment and release. Thus, it significantly reduces time consumption and expenses on maintenance by keeping your apps up to date. Enhanced Time-to-Market With Xamarin, you can code application logic once and then share it across all mobile operating systems. Thus, there is no need to repeat the same procedure for multiple platforms, which reduces the time required for building a software. Moreover, if there are any issues after-sales maintenance, it needs to be fixed only in one application which is easy to do. Conclusion: In a world where different mobile platforms exist, a toolset is required which supports multiple platforms with minimal efforts. We get this with Xamarin, king of cross-platform development. Its rich features and resulting benefits allow developers to develop flawless cross-platform native applications.  
5 Reasons to use Xamarin for cross-platform application development

5 Reasons to use Xamarin for cross-platform application development

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The mobile development market is growing at an exceptional rate due to huge consumer mobility and is divided among iOS, Android, Windows and other mobile operating systems. According to IBM research, ...
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Microsoft and Amazon Partnership to integrate Alexa and Cortana

Microsoft and Amazon are now partnering to integrate their digital assistants Cortana and Alexa respectively. Such kind of integration will allow Alexa users to access unique Cortana features. Microsoft has mostly implemented Cortana for direct access to its Office products. Now with this cross platform integration of digital assistants, Alexa will also get this functionality via Cortana. Along with this, Cortana users will also be able to access Alexa features which are missing in Cortana. “The world is big and so multifaceted. There are going to be multiple successful intelligent agents, each with access to different sets of data and with different specialized skill areas. Together, their strengths will complement each other and provide customers with a richer and even more helpful experience,” said Jeff Bezos, Founder, and CEO, Amazon in a press statement. As described in the press statement, people are just required to turn on their echo devices and say “Alexa, Open Cortana” and windows 10 users will say “Cortana, Open Alexa”. The entire integration will be little awkward initially. Satya Nadella also added, “Ensuring Cortana is available for our customers everywhere and across any device is a key priority for us”. Almost all the tech giants including Apple, Amazon, Google, and Microsoft have created rival digital assistants. This kind of partnership or integration is a signal towards better usage of these digital assistants. The integration is most likely to happen later this year.  
Microsoft and Amazon Partnership to integrate Alexa and Cortana

Microsoft and Amazon Partnership to integrate Alexa and Cortana

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Microsoft and Amazon are now partnering to integrate their digital assistants Cortana and Alexa respectively. Such kind of integration will allow Alexa users to access unique Cortana features. Microso...
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Google releases Android 8.0 Oreo - Few Important features to Note

Image Source: Android Official On August 21, Google officially announced the release of the next major version of Android, Android 8.0 Oreo. It is available in beta version and compatible with the Pixel XL and Google Pixel, as well as the Nexus 6P and Nexus 5X. "The official OTA to Android O for Pixel will likely drop in the first week or two of August. A bit earlier than Nexuses / Nougat last year," said David Ruddock, from Android Police. He added that the info comes from a "reliable source". Updates for other tablets and smartphones will depend on handset manufacturers such as OnePlus, Huawei and Samsung, with a few undertakings to update certain devices to Oreo. Sameer Samat, VP of product management for Android and Google Play, described the Oreo as “smarter, faster and more powerful than ever”. “It comes with new features like picture-in-picture and Autofill to help you navigate tasks seamlessly. Plus, it’s got stronger security protections and speed improvements that keep you safe and moving at light speed. When you’re on your next adventure, Android Oreo is the superhero to have by your side (or in your pocket!),” he said in a blog post. Android Oreo is more secure with tighter app install controls, Google Play Protect built in, and security status front and center in settings. It also supports Android Instant Apps which allows users to run apps instantly without downloading it. Let’s have a look at the things which got better with the new Android Orea 8.0:- Background Limits Google has promised better battery life with Android 8.0. This new OS will treat background processes in a different way, which means, some applications will work differently. Before Android Oreo, developers created applications that listen to a broad range of system broadcasts. Earlier, if a broadcast of change in connectivity occurred, dozens of apps used to wake up, creating a negative impact on the system performance. Now, developers will use more specific receivers and job schedulers to ensure specific apps should wake up in the background. Picture-in-Picture The new feature Picture-in-Picture creates a small window for YouTube video and it will exist on the top of the main display. The feature was originally developed in Nougat but then it was only available on Android TV devices. Now it will be available on Phone and Tablet too. The feature will now allow people to check e-mails while the video will be playing in the background. Google Play Protect To keep users safe from malicious applications, Android Oreo has introduced a new feature called Google Play Protect. It will stop the spread of potential malware through mobile devices. Every day Google Play Protect scans 50 billion apps and removes harmful apps automatically. Google Play Protect also has a unique feature called Find My Device. This helps in remotely locating or wiping the device in case the user loses it. In this way, the user can avoid his/her personal information falling into wrong hands. Smart Text Selection Google has now integrated machine learning with Android 8.0 to recognize entities like addresses, telephone numbers, and email addresses and making it easy for users to copy and paste. Autofill APIs Remembering long passwords is a very difficult task. In this update, apps can register as auto-fill providers with the system. Users can select the auto-fill provider in their preferred languages with required input settings Android will ask for login details from the app whenever it is required. The system also verifies the fingerprint or other secure unlock methods before loading any data.  
Google releases Android 8.0 Oreo - Few Important features to Note

Google releases Android 8.0 Oreo - Few Important features to Note

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Image Source: Android Official On August 21, Google officially announced the release of the next major version of Android, Android 8.0 Oreo. It is available in beta version and compatible with the ...
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6 Best ReactJS based UI Frameworks

React.js ( sometimes termed as ReactJS or simply React) is an open source JavaScript library that provides a view for data rendered as HTML. Developed by Facebook in the year 2013, React.js has gained a lot of attraction in developer’s community. A lot of well-known companies including Facebook, Instagram, Netflix, Feedly, Airbnb, etc have incorporated React in their core technology. Now it's time for the developers who are having prior experience in ReactJS to start building their own web applications. To make it little easier, React provides a set of tested full-fledged front-end frameworks created for fast application prototyping and building. We have clubbed few of the important ReactJS based UI frameworks to help developers in starting their initial web or mobile applications. - Material UI Material UI is a set of React Components implemented with Google’s Material Design Guidelines. Out of hundreds of framework, Material UI has the most refined implementation of Material Design. Material UI is available as an npm package and can be installed in the project by simply running npm install material-​ui Then users can add any component of Material UI into their projects. - React Bootstrap React Bootstrap is defined as a library of reusable front-end components. Its official documentation says, “The most popular front-end framework, rebuilt for React”. React - Bootstrap component library defines every single function in a single place which is same as ReactJS. For demo purpose, developers can find all the component library under the components section. - React Foundation Foundation from Zurb is both feature-rich and easily customizable library. On the other hand, React.js is the most popular for its simplicity. React Foundation is basically the wrapping up of Foundation’s every part into re-usable React components following the framework’s best practices. The main objective behind developing React Foundation is ease-of-use and extensibility. - React Semantic UI Semantic UI React is the official integration of Semantic-UI-React. Semantic is a framework that helps in creating beautiful and responsive layouts using human-friendly HTML. Semantic UI treat both words and classes as exchangeable concepts. Classes use syntax from natural language like noun/modifier relationship, plurality, word order to have a link between concepts intuitively. Semantic also uses simple phrases called behaviors that trigger functionality. - React Toolbox React Toolbox is a set of React components having an implementation of Google Material Design specification. React Toolbox is basically built on CSS Modules, Webpack, and ES6. By default, it uses CSS Modules to import style sheets written in SASS. - Ant Design Ant Design consists of enterprise-class UI design language for web applications including a set of high-quality React components out of the box. The language is written in TypeScript with complete defined types. Ant Design supports server-side rendering and works in all modern browsers and Internet Explorer 9+.
6 Best ReactJS based UI Frameworks

6 Best ReactJS based UI Frameworks

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React.js ( sometimes termed as ReactJS or simply React) is an open source JavaScript library that provides a view for data rendered as HTML. Developed by Facebook in the year 2013, React.js has gained...
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