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If you are into designing web applications, deciding a JavaScript framework for it can be a tedious and overwhelming task. React and Angular are JavaScript platforms which are quite popular these days. These two frameworks come from a lineage of two powerful competitors – Google and Facebook. React has already established itself in the industry but Angular is relatively new to the game. The performance of React vs. Angular is often debated upon.

Frameworks and libraries are distributed with different licenses. There are some licenses which are somewhat flexible and allows for adjustments according to the requirements. They are known as open-source products and there are other licenses which do not allow for the designing of commercial applications or the flexibility of editing the content after its creation.

Both Reactjs and Angularjs are open-source products and when it comes to the popularity of React vs. Angular, both are used by major brands.

You can see here the Google trends comparison graph of Angular vs react.

Before you even move even a step ahead, it is suggested to glance through the synopsis of the Angular Framework and the React Library to decide on your next project.

Check here the comparison of both angular and react.

Technology React Angular JS Angular 2
Usage It is used for setting up needed processes and introducing to the quality standards for preventing the errors and flaws in an app. It is used for For assuring the app works to the requirement and specs before its final launching. It is used for identifying and correcting the bugs as well as errors.
Company Facebook Google Google
Category Open source JS Library JavaScript framework JavaScript framework
Toolchain High Low High
Language JavaScript, JSX JavaScript, HTML TypeScript
Learning Curve Low High Medium
Packaging Strong Weak Medium
App Architecture None MVC Component based
Data Binding One way data binding Two way data binding Two way data binding
DOM Virtual DOM DOM, Regular DOM, Regular
Last Version React 15 Angular JS 1.6.0 RC2 Angular version 4.3

Let’s see more about Reactjs and Angularjs.

About Reactjs

React was released in 2013 by Facebook. It supports JavaScript languages and renders both client and server-side data. Its architecture is component-based and follows a one-way data binding technology. Its DOM is virtual however its learning curve is relatively low.

Advantages of Reactjs:

  • React allows you to use HTML codes as it comes forward with JSX. You can practice HTML tags and syntax for rendering subcomponents.
  • It offers the ability to compound the components of the app in a single time file, and it also promoted the development of machine-readable programs.
  • React comes with an ideal setup for app developers and it had led to a large number of developers using React Native for application development.
  • React has a prompt rendering feature that gives it a slight edge over the Angular JavaScript. It consists of various approaches to lessen the amount of DOM operation and thereby speeds up the updating process, making it more efficient.
  • React has a Virtual DOM which can help developers manage an extensive database.
  • React is a purely JavaScript based library product. A primary difference is that Angular is a subset of HTML and React is not.
  • React is a choice that you make when you are looking for reliable, intensive and straightforward programming. It is a relatively more advanced language than Angular.

Disadvantages of Reactjs

  • A traditional MVC framework like Rail needs configuration and integrating Reactjs into it slows down the development time and process.
  • If you combine the advantages and disadvantages for React, you will see that the framework might be suitable for specific applications and not work for the rest. Every app is different.

When to use Reactjs?

When there is a lot of dynamic content in your application that is when React would be the right choice. Many popular brands like Instagram and Facebook prefer to use ReactJs to base their mobile apps on because of its dynamic nature.

Sometimes, adopting React may make sense over using Angular and vice versa. Here are a few brands which have used Reactjs: Uber, Dropbox, Netflix, Instagram, PayPal, and Flipkart.

About Angular

Angular was released in 2010 by Google. It supports JavaScript languages and renders both server and client-side data. Its architecture is component-based, and it is usually used for templating Typescript files. It follows a two-way data binding technology, and it works on a real DOM and has a steep learning curve compared to React is relatively low.

Advantages of Angularjs

  • Angular is known for its community and developer support services. Angularjs has brought in a rise in demand for its framework because of its support factors.
  • The Angular framework runs on all browser environments regardless of its platforms.
  • Angular has established itself as a reliable framework because it includes off-the-rack tools and it also has robust components which are evolved in Juxtapose.
  • Angular comes with a Bi-directional data binding feature that is, in fact, the primary difference between Reactjs and Angularjs. It disperses influence after every set of data changes.

Disadvantages of Angularjs:

  • Angular does not consist of extensive, all-inclusive documentation or a clear manual.
  • It also has a steep learning curve which is one of its main drawbacks.

When to use Angularjs?

When you require your app to be compatible with all the browsers that is the best time you use Angular. It even helps your app consistent with browsers older than the IE8. There has also been a recent release of the Angular 5.0 in the market and it has undoubtedly attracted a lot of attention from developers especially with its performance boost features and server-side rending support services. If your mobile application lies between the complexities of low to medium, Angularjs is the best way to go.

Some of the popular brands using Angularjs are: NASA, HBO, Nike and YouTube.

Aspects to consider when choosing between React vs. Angular

  • MVC Pattern:-
    Dividing the application into distinct and easily modifiable elements make it easier to reduce the line of codes, and in the end, it increases the quality of the result of the product. React only has the view component of the MVC which can increase the line of codes but Angular is developed according to the MVC architecture.
  • Templating:-
    There are various templates used to create UI. When you are developing a JavaScript product, you would want to take advantage of them. React makes use of the templates in the JSX file whereas Angular uses templates in the TypeScript file.
  • Data Binding:-
    Data binding is a feature that helps you establish a connection between the UI and the business logic of the app. React implements a one-way data binding whereas Angular uses a two-way coupling which lets the framework connect the model data to the DOM via the controller. This affects the performance of the app. However, in React, when the data is directed only one way, debugging the app of errors becomes more natural, especially for applications that are quite large.
  • Rendering:-
    You can render data is two ways – client side and on the server side. Delivering through the client side inversely affects the page loading time. Therefore, it is suggested that use a framework that provides data through the server side. Both React and Angular use server side.
  • Performance:-
    Since React has a one-way data binding, it does not influence the performance when you try to develop complex applications. When you use Angular, you face this issue of the app performance. Additionally, Reactjs application developers have added a built-in virtual DOM feature that lets the server save a light ‘DOM tree’ which leads to less loading time on the browser.

Aspects to consider when you are determining the performance between React vs. Angular

  • Packaging:-

    It is all about the flexibility and capability of a developer to deploy a code the way you want it to run. If you want to achieve a faster loading time, developers much first aim at loading the minimum number and then continue when its demand increases. This gives you the ability to develop features without degrading the loading time.

    When it comes to React vs. Angular, React allows developers to make the best use for slower loading pieces of code. Its library also enables working with solutions like web pack. Angularjs offers a limited ability to control the packaging, and as a result, it ends up looking like assembly code. Thereby, Angular is comparatively more rigid. So, while dealing with packaging, React is better.

  • Learning Curve:-

    Angularjs has a steeper learning curve compared to Reactjs and so, it is not easy to master. If you are a professional developer, this will be easier to understand. Angular has a complicated lifecycle, and you need to deal with its unintuitive link and compile it. React on the other hand has a lower learning curve and takes lesser time for developers to understand its one-way data flow. Its library has very few lifecycle methods and you hardly ever have to read it. So, regarding the learning curve, React is better.

  • Model Complexity:-

    Model complexity means how you would structure your app data model when it is represented by the view. When it comes to this, Angular is considered quite sensitive when you deal with its scope because of its copy and compare feature. This means that it will restrict you from using large app models. However, the outcome will come with an advantage of making the code testable and simple. React gives you the option to choose without impacting the performance of the app. So, regarding model complexity, both React and Angular are good.

  • Reuse of Code:-
    React lets you manage your app code as you like but Angular consists of a series of ready to use elements. Even if it has priority collisions and namespaces, Angular is always prepared to employ more elements. So, regarding the reuse of code, Angular is much better.
  • Templating:-
    Templates are mostly termed as building blocks of mobile apps. They have a lot of customer information and flows that are developed with the app’s built-in, ready-made blocks. However, they are not reusable. So, regarding templating, Angular is better.

Key Takeaways

Both AngularJS and React are equally useful for writing applications. But they are entirely different frameworks to use. Some programmers may say that AngularJS is superior to React and vice versa. What’s in actuality best for an in-hand project is the way you utilize these frameworks.

Working with React seems a slight simpler at the starting point, as you write old-school JavaScript and use more HTML around it. However, there are many added tools you will have to take hold of like Flux. On the other hand, AngularJS works differently around HTML with a more organized approach. That’s why we may see typical and diverse syntax that looks debatable at initial sight. However, once you get familiar to AngularJS, you will surely get assistance from its unique and powerful features.

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Written By : Technostacks

The global view-point of machine learning frameworks is constantly advancing. Artificial intelligence combined with the correct profound learning system has intensified the general size of what organizations can accomplish and get inside their areas. Also, with an ever-increasing number of organizations hoping to scale up their tasks, it has turned out to be indispensable for any organization to assimilate both machine learning and also prescient examination.

Every system here works alternately for various purposes. Here, we will take a quick look at the best Machine Learning Frameworks to give you a superior thought of which method will be the ideal fit or come helpful in understanding your business challenges. And further, help you in creating machine learning applications with frameworks as well as the most popular machine learning frameworks on which the scientists and the developers are working.

1. TensorFlow

TensorFlow

Currently, TensorFlow is the top in the list of Machine Learning frameworks. Most developers are using Tensorflow because it has a great support community and many inbuilt features.

It is outstanding amongst other profound learning structures and has been embraced by a few Goliaths, for example, Airbus, Twitter, IBM, and others for the most part because of its exceedingly adaptable framework engineering.

The most outstanding use instance of TensorFlow must be Google Translate combined with capacities, for example, common dialect handling, content arrangement/rundown, discourse/picture/penmanship acknowledgment, anticipating, and labeling.

TensorFlow is accessible on both work area and versatile and furthermore underpins dialects, for example, Python, C++, and R to make profound learning models alongside wrapper libraries.

TensorFlow accompanies diverse instruments that are broadly utilized. TensorBoard is used for compelling information perception of the system demonstrating and executing TensorFlow serving for the quick arrangement of new calculations/tests. Along with that, it holds a similar server engineering and APIs.

It likewise gives coordination to other TensorFlow models, which is unique about traditional practices and can be reached out to serve different model and information composes.

In case you are stepping towards profound learning, it is an easy decision to decide on TensorFlow given that is Python-based, is supported by Google, and comes stacked with precise documentation and walkthroughs to be managed well.

2. Caffe

Caffe

Caffe is a deep learning system that is strengthened with interfaces like C, C++, Python, and MATLAB and also the order line interface.

It is outstanding for its speed and transposability and its pertinence in displaying convolution neural systems (CNN). The most significant advantage of utilizing Caffe’s C++ library (accompanies a Python interface) is the capacity to get to access systems from the profound net archive Caffe Model Zoo that are pre-prepared and can be utilized promptly. With regards to demonstrating CNN’s or illuminating picture handling issues, this ought to be your go-to library.

Caffe’s greatest USP is speed. It can process more than 60 million pictures every day with a solitary Nvidia K40 GPU. That is 1 ms/picture for deduction and 4 ms/picture for learning — and later library adaptations are even quicker.

Caffe is a prominent profound learning system for visual acknowledgment. Not with standing, Caffe does not reinforce fine-granular system layers like those found in TensorFlow or CNTK. Given the design, the general help for broken systems and dialect displaying its very poor, and building up complex layer composes must be done in a low-level dialect.

3. Microsoft Cognitive Toolkit

Microsoft Cognitive Toolkit

The Microsoft Cognitive Toolkit (beforehand known as CNTK) is an open-source profound learning system to prepare scholarly learning models. The tool is prominently known for simple preparing and the blend of mainstream, which demonstrates crosswise over servers. It performs proficient convolution of neural systems and making for the picture, discourse, and content-based information. Like Caffe, it is supported by interfaces, for example, Python, C++, and the order line interface.

Given its smarter utilization of assets, the usage of fortification learning models or generative ill-disposed systems (GANs) should be possible effectively utilizing this toolbox. It is known to give higher execution levels and adaptability when contrasted with toolboxes like Theano or TensorFlow while working on multiple types of machines.

Contrasted with Caffe, with regards to concocting new complex layer composes, clients don’t have to execute them in a low-level dialect because of the fine granularity of the building squares. The Microsoft Cognitive Toolkit underpins both RNN and CNN sorts of neural models and along these lines is equipped for taking care of pictures, penmanship, and discourse acknowledgment issues. As of now, because of the absence of help on ARM engineering, its capacities on versatile parameters are genuinely restricted.

Related Article:- How Can Machine Learning Helps In Agriculture Industry

4. Torch

Torch

Torch is a logical figuring structure that offers wide help for machine learning calculations. It is a Lua-based profound learning system and is utilized generally among industry goliaths, for example, Facebook, Twitter, and Google. It utilized CUDA alongside C/C++ libraries for handling and was fundamentally made to scale the creation of building models and give in general adaptability.

Starting late, PyTorch has seen an abnormal state of appropriation inside the profound learning structure network and is viewed as a contender to TensorFlow. PyTorch is fundamentally a port to the Torch penetrating learning system utilized for building profound neural systems and executing tensor calculations that are highly advanced along with their multifaceted nature.

Instead of Torch, PyTorch keeps running on Python, which implies that anybody with an essential comprehension of Python can begin without anyone else’s profound learning models.

Given PyTorch structure’s building style, the whole profound demonstrating process is far more natural and additionally straightforward contrasted with Torch.

5. MXNet

MXNet

You can’t ignore MXNet when preparing the list of best machine learning Frameworks. MXNet (articulated as blend net) is a profound learning system upheld by Python, R, C++, and Julia.

The brilliance of MXNet is that it enables the client to code in an assortment of programming dialects. This implies you can prepare your profound learning models with whichever dialect you are agreeable in without discovering some new information sans preparation. With the backend written in C++ and CUDA, MXNet can scale and work with a horde of GPUs, which makes it fundamental to endeavors. A valid example: Amazon utilized MXNet as its reference library for profound learning.

MXNet underpins long here, and now a memory (LTSM) organizes alongside both RNNs and CNN’s. This profound learning structure is known for its capacities in imaging, penmanship or discourse acknowledgment, determining, and NLP.

Related Article:- Machine Learning Vs. Artificial Intelligence

6. Chainer

Chainer

Exceptionally great, dynamic and intuitive, Chainer is a Python-based profound learning structure for neural systems that are planned by the run procedure. Contrasted with different structures that utilize a similar technique, you can change the systems amid runtime, enabling you to execute discretionary control stream articulations.

Chainer sustains both CUDA calculations alongside multi-GPU. This deep learning system is used principally for assumption investigation, machine interpretation, discourse acknowledgment, and so on utilizing RNNs and CNN’s.

Related Article:- How AI & ML have been a Blessing for the Banking and Financial sector

7. Keras

Keras

Keras is falling under the category of open source machine learning frameworks Known for being moderate, the Keras neural system library (with a supporting interface of Python) supports both convolution and repetitive systems that are equipped for running on either TensorFlow or Theano. The library is composed in Python and was produced keeping brisk experimentation as its USP.

Because of the way the sensor flow interface is designed it is little bit testing combined with the idea that it is a low-level library that can be many-sided for new clients. Keras was worked out to give a short-sighted interface to the reason for quick prototyping by developing compelling neural systems that can work with TensorFlow.

Lightweight, simple to utilize, and extremely direct with regards to building a profound learning model by stacking various layers: that is Keras more or less. These are the specific reasons why Keras is a piece of TensorFlow’s center API.

The essential use of Keras is in characterization, content age and outline, labeling and interpretation, alongside discourse acknowledgment and the sky is the limit from there. If you happen to be a designer with some involvement in Python and wish to plunge into profound learning, Keras is something you should look at.

Key Takeaways

It is apparent that the approach of profound learning has started with numerous tools who utilize instances of machine learning and human-made reasoning. Separating assignments in the least difficulty of course and with the end goal of helping machines work more productively has been made feasible by insightful learning.

Some of the Machine Learning Frameworks from the above rundown would best suit your business prerequisites? The response to that lies on various variables or on the off chance that you are looking to merely begin, at this point with a Python-based profound learning system like TensorFlow or Chainer.

In case you are searching for something more, at this point with assets like speed and swift utilization alongside the intelligibility of the prepared model you ought to check out all the parameters before choosing a profound learning system for your business needs.

Written By : Technostacks

Augmented Reality is one of the best things and the most exciting technologies around for the people in this generation. AR was first featured in movies and people thought it is only restricted to entertainment purpose which is not the case today. In fact, Best Augmented Reality Apps for iPhone and Android have made a great impact on our real life. The inception of AR has made learning easy, gaming all the more fun, with the realistic looking scenarios and the 3D view of maps while driving and getting to know the predicted time you will take to reach your targeted destination.

All this is possible through this amazing technology and related tools. There is no second thought that AR applications for Android and iPhone have to do much more in the near future. Let us have a look at the Best Augmented Reality Apps that presently exist in the diverse application development marketplaces and how they can be utilized to change some of the needed set-ups.

1. MondlyAR

MondlyAR

Image Source:- producthunt.com

This App has transformed the way how learning a different language was pursued in the past. You needed books, dictionaries, and a tutor and spend a good amount of money for a class of a few hours in a week.

MondlyAR eliminates the tedious long-term affair and brings to you the first ever AR language learning App that uses speech recognition and tries to supplement your learning experience with the human interaction. The virtual learning assistant helps you to learn phrases and words hence making the app more interactive by leveraging the speech recognition technology.

The app is fun and exciting as it teaches you how to pronounce the words in its respective language. MondlyAR is available for both Android and iOS users. One can learn Spanish, English, French, German, Italian and 20 more languages which get added to new updates.

2. Ingress

Ingress

Image Source:- beccarama.com

If AR is your recent thing then you would not prefer anything else then using AR to play games. Ingress is one such thing in the gaming world that you should check. This app engrosses virtual world where you need to choose a side – the Resistance or Enlightened. This mission-based app makes you find virtual portals in the real world and you need to capture them.

The app is based on a complex sci-fi world and requires you to move around in the real world in order to capture and protect locations. Though this app lacks accessibility in comparison to other apps available in the market, however, it was able to capture a huge community in just a few months of being launched. The app is available on Android and iOS both.

3. PokemonGo

PokemonGo

Image Source:- uploadvr.com

Without mentioning Pokemon Go, the list of the best augmented reality apps would be incomplete. The app immediately became every game hot favorite. The unique concept of going out in the real world, walking around and catching Pokemon – the unique concept brought up by Niantic’s through AR is a must have in every games phone.

The app uses your phone’s GPS location to mark your location whereas the camera is used to locate Pokemon in the real world. The game is easy and does not need to require many instructions to read. This easy to play and understand the game has been the best augmented reality game app available on the Play Store and the App Store.

4. Amikasa

Amikasa

Image Source:- komando.com

How about an app helping you to style your room or office instead of an interior designer who would charge you a good amount even for consultation? Amikasa is at your rescue and is a great virtual assistant help your style your room before you decide to buy a piece of furniture. Be it your office, garden area, hall, kitchen or bedroom with the help of your iPhone or iPad’s camera you need to simply walk around the space and place 3D models of various furniture pieces to understand how it would look in the real world.

The app allows you to change the color of the furniture based on the color of the room. You can buy the furniture right through the app. It gives the facility of sharing your room design with your family and friends to ask for an opinion. For now, the app is available only on the App Store.

5. Google Translate

Google Translate

Image Source:- departsmart.org

Google Translate is traveler’s favorite app. It enables one to have a conversation with people even when you do not have a common language. The app is not restricted only to spoken words. The app allows users to even translate road signs, menu and other texts on the go which are in a different language with the use of phone’s camera.

Not only that, the AR feature allows translating your handwriting audio or even a real-time conversation with someone with a different language. Along with the features the app has visual flair and easy to use. The app is available on the App Store and the Play Store.

6. View Ranger

View Ranger

Image Source:- harveymaps.co.uk

If you are one of those adventurous souls, then you should definitely try out this app. ViewRanger app is designed for hikers who are in the look out of the next great adventurous trail.

The app has an inbuilt library that allows you to search through; the GPS feature identifies your location and suggests the nearest trail. The inbuilt street, aerial, satellite and terrain maps helps you in locating the latitude and longitude. Over nine million locations across the world have been listed in the app and the database is been updated on a regular basis.

7. SketchAR

SketchAR

Image Source:- microsoft.com

Everyone has a little artist within, however, time doesn’t permit to practice that and turn it into a hobby. There come SketchAR to turn your dream into reality.

SketchAR brings out the creative side of yours through Augmented Reality. All you have to do is simply draw a few circles onto the paper and the app allows you to trace around it. You will have to properly trace those lines, initially you will struggle to match the lines but eventually, you will get hold of the techniques.

In fact, holding a phone in one hand drawing with the other is pretty uncomfortable however it’s worth trying. Mostly ARCore phone is the best for this app. SketchAR is available on Play Store and App Store both.

8. ROAR

ROAR App

Image Source:- blog.theroar.io

ROAR is a shopping adviser for consumers. This app is of great benefit for all the segments i.e. business, consumers and retailers. You can click pictures of foods and drinks and instantly get the price, ingredients used in its preparation and see reviews from people who have tasted it.

Consumers can compare the same product from various brands for the price and they can also purchase the product right from the app, additionally, people go bonkers when they can buy movie tickets simply by scanning the movie poster. The app comes up with some great features in order to make the in-app experience fun. It is available on both iOS and Android.

9. NightSky / Star Walk

Star Walk

Image Source:- youtube.com

Night Sky on iOS and Star Walk on Android, this app offers an amazing AR experience for stargazing and astronomy. The app uses your current location and through the mobile phone’s orientation provides an accurate star map based on the geo-location.

This map is usually designed to layer on top of the surrounding by using the AR functionality. This app is considered to be the best for learning and educating the astronomy.

10. HOLO

HOLO App

Image Source:- theverge.com

Holo is an interactive app for both Android and iOS users allowing users to place various holographic figures into a scene for capturing video and pictures. The app has a limitation of only one holographic character per picture.

However, it is one of the most preferred AR apps because of its wide choice of preloaded content available. All your creations can be shared directly from the app to popular social media platforms.

Key Takeaways

Technology has taken over every walk of people’s lives in recent times either it’s discovering the most innovative mobile applications or creating best augmented reality games. So, it very well seems to be apparent that in near future Augmented Reality Apps will become an integral part of people’s lives. Hence it is wise to embrace the change it brings to our life as the main aim of Augmented Reality is to transform the world into a much better place for the coming generation.

Most of the AR apps are absolutely free which leaves no scope of ignoring this evolution. We encourage everyone to make the most use of these apps today and experience a different version of reality. Hope this best augmented reality apps article helps you to explore your knowledge.

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Written By : Technostacks

Machine learning is a trending technology nowadays and it can be used in modern agriculture industry. The uses of ML in agriculture helps to create more healthy seeds.

The principle that Arthur Samuel used earlier in machine learning experiments are used in today’s modern agriculture. Artificial machine learning in agriculture is one of the fastest growing areas. Artificial techniques are being used in the agricultural sector to increase the accuracy and to find solutions to the problems.

Agriculture plays a very pivotal role in the global economy of the country. Due to the increase in population, there is constant pressure on the agricultural system to improve the productivity of the crops and to grow more crops.

A) Machine Learning Methods

In machine learning agriculture, the methods are derived from the learning process. These methodologies need to learn through experiences to perform a particular task. The ML consists of data that are based on a set of examples. An individual example is defined as a set of attributes. These sets of characteristics are known as variables or features. A feature can be represented as binary or numeric or ordinal. The performance of the machine learning is being calculated from the performance metric.

The performance of the ML model improves as it gains experience over time. To determine the performance of ML models and the machine learning algorithms agricultures various mathematical and statistical models are used. Once the learning process is completed, then the model can then be used to make an assumption, to classify and to test data. This is achieved after gaining the experience of the training process.

agriculture with Machine Learning

Image Source:- mindbowser.com

Machine Learning Functions

It can be divided into two categories, namely supervised and unsupervised learning.

  • Supervised Learning
  • In this machine learning agriculture method, the input data is represented with examples to the corresponding outputs. The primary goal of this function is to create a rule that will map the inputs to the corresponding outputs. In some cases, the inputs might not be available that may lead to missing output. The trained model is then used in supervised learning to predict the disappeared production and then the data is being tested.

  • Unsupervised Learning
  • In this machine learning agriculture technique, there is no difference between the trained models and the test sets, while unlabeled data is being used. The goal of this method is to find the hidden patterns.

Related Article:- How AI & ML have been a Blessing for the Banking and Financial sector

B) The Machine Learning (ML) Evolution in Different Areas

Machine learning is evolving along with big data technologies and other fast computing devices. They are growing to create new opportunities to understand the various data processes related to the environmental functions of agriculture. Machine learning can be defined as the scientific method that will allow machines the ability to learn without programming the devices. Machine learning is used in various scientific areas such as Bioinformatics, Biochemistry, Medicines, Meteorology, Economic Sciences, Robotics, Food Security and Climatology.

C) Uses of Machine Learning (ML) in Agriculture

Artificial Intelligence is being used in various sectors from home to office and now in the agriculture sectors. Machine learning in agriculture used to improve the productivity and quality of the crops in the agriculture sector.

  • Retailers
  • The seed retailers use this agriculture technology to churn the data to create better crops. While the pest control companies are using them to identify the various bacteria’s, bugs and vermins.

  • AI is used to boost the yield of crops
  • The AI technologies are used to determine which corn and which conditions will produce the best yield. It will also determine which weather condition will give the highest return.

  • AI helps to identify bug hunters
  • One of the companies named Rentokil is using AI to kill all the bugs and vermin. Other companies are making use of Android app which is developed by Accenture to find bugs. The app takes the pictures of the bug and runs the app called as PestID. When a bug is found app will provide an immediate solution which helps the technician to take further actions. It will also recommend the chemical to be used to kill the bugs.

Related Article:- Machine Learning Vs. Artificial Intelligence: Understanding The Key Differences

D) Most Popular Applications of Machine Learning (ML) in Agriculture

Let us look at the various applications of machine learning in agriculture.

  • Agriculture Robot
  • Most of the companies are now programming and designing robots to handle the essential task related to agriculture. This includes harvesting crops and works faster than then human laborers. This is the best example of machine learning in agriculture.

    machine learning farming robot

    Image Source:- yourvippartner.com

  • Monitor crop and soil
  • Companies are now making use of technologies and deep learning algorithms. The data are then collected using the drones and other software to monitor the crops and also the soil. They also use the software to control the fertility of the soil.

    By making use of new technologies in agriculture, farmers can find effective ways to save their crop and also protect them from weeds. Companies are developing robots and automation tools to achieve them. Agricultural spray machines are designed, See and Spray robot that is being developed by Blue River Technology will monitor and spray accurate weeds on the plant like cotton. The precise amount of spraying can help to reduce herbicide expenditures.

    Plant breeders are looking out for a particular trait on a regular basis. They look up for the qualities that will help the crops to use more water efficiently, use the nutrients and also adapt to the climate changes or any diseases. If the plant needs to give the desired result the scientist need to find the right gene. Find the correct sequence of the gene is difficult.

E) Machine Learning (ML) Models Used in the Agriculture Industry

  • The agricultural farmers are now taking advantage of the machine learning models and their innovations. Using AI and machine learning is good for the food tech segments.
  • The Farmers Business Network that is being created for the farmers a social network will make use of the ML and the analytic tools to drive the results of data on pricing.
  • Robots are now managing the crops and also monitoring them.
  • Sensors are helping to collect the data related to crops.
  • According to research if AI and ML are being used in agriculture, then the agriculture sector will grow in the coming years.

F) Rising Opportunities of Machine Learning (ML) in Digital Agriculture

There is a rise in digital agriculture, which uses a secured approach to give maximum agricultural productivity by reducing the impact on the environment. The data that is generated in modern agriculture is based on various sensors that will help in better understanding of an environment like the crop, soil and the weather conditions and also about the agricultural machines. These data will help us to take quick and fast result-oriented decisions. To yield more, we need to apply machine learning to agriculture data.

G) Real-life ML Example

A Mexico based Startup Company Descartes Labs are combining the satellite images, ML, Cloud computing and sensors to a better understanding of industries related to agriculture and energy. The company uses new technology in agriculture to discover where crops are situated and how good and healthy the crops are.

The machine learning tools which were reserved for some institutions are now accessible to all small and capable members. A small startup is making use if AI and machine learning to bring change in the modern agriculture sector. They are trying to reshape the contemporary agriculture sector by making use of innovative technologies.

Moving Forward

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Written By : Technostacks

Android’s leading strength is its app ecosystem. There are a digital ton of Android apps. Both technical and non-technical people download them billions of times. Some of them are cost-effective and some of them are not. More often than not, the best apps will cost you some bucks.

However, there are a lot of incredible options that don’t cost you. These services are typically supported by online advertising, business sponsorships or some other sort of financial planning.

Here’s your prospect to stock up on some beyond doubt exceptional stuff. These are the best free Android application available which are the finest of all time, so most of these should not astonish you.

Why Some of the Android apps have Turned as an Essential Part of our Lives

So here we are, ladies and gentlemen, with a unique list of top Free Android Apps that stand at the top of the pantheon. The apps that we have listed here are permeating with Android and there are a few apps that become the most important part of our lives. The ones that we have listed here we assume that you might already have them in your phone. Since Google play store has tons of Android apps their usefulness is limited to the habits of the people using it in their daily lives. Without any further delay let’s take a look at the best free android apps of 2018 and upcoming 2019.

We are pretty sure you all will be familiar to these as most of the apps provide similar kind of functionality but what makes these apps make a place in the most downloaded Android apps is what makes the real difference. So, let us take a look at them and explore these must have android apps with their diverse features and functionalities.

Note: We have made this list by making an allowance for user ratings, application features, functionalities, and popularity. You are free to pick any other option that suits your requirements for business or daily usage.

10 Best free Android Apps You Should Walk Around

1. Google Duo

Google Duo

Google Duo is one of the best voice and video calling apps for Android developed by Google. It has a simple interface which can be learned easily. The easy to log in and verify option can get you going instantly and you are all set to make free video calls across the world.

This is just like a standard phone call and of course, the other person needs to have a Google Duo account and you can talk to that person sitting in any part of the world absolutely free. The minimum requirement is a working WIFI or internet connection that will give you a flawless video calling experience.

It also has a “Knock-Knock” feature which gives you the caller before receiving the call. This is the most downloaded android apps.

2. Google News App

Google News App

When you think about the best free android apps, then you can’t ignore the Google News Application. It keeps you updated with the latest and the most relevant news in the news feed. The AI technique used for this app brings to you the news of your interest from across the world.

It is one of the must-have android apps in 2018. The special ‘for you’ tab gives you a personalized news window where you will get a full coverage of news that interests you. Isn’t it interesting?

3. Evernote

EverNote

Evernote app is one of the top notes taking application on the play store. It is a cross-platform application that allows you to take notes in various formats that includes text, photos, audio, video, sketches and more.

In today’s hectic world forgetting things has become a very normal thing hence here comes the smart note taking app at your rescue that syncs almost all your devices to keep up with your workflow. The quick widget feature on the home screen allows you to access the notes quickly.

4. AppLock

AppLock

AppLock is a free android app which is simple and the most important app everyone should have if you save sensitive data on your phone. This app allows you to lock your preferred app up tight with a password so that no one can miss using your phones.

There are two options in the app one which is absolutely free and another one which is available to premium users which come at a minimum cost and users can use the app without any ads. Keep your personal data in the phone secured by AppLock.

5. Gboard

Gboard

It is one of the best apps for android which is the top official keyboard app introduced by Google. This is easy to use and effective app which can be used without making the typing task complex. Just like any other normal keyboard features like gesture typing, light theming, voice typing, emoji search, GIF and more – Gboard application allows you to Google search without leaving the keyboard or any app that you are using at that moment.

The smart sync feature allows you to sync between the devices so that whatever you have saved remains with you. This is a must have android application for those who are mostly in the fields and have to sort out most of their work over the mobile phone. It is one of the best free android app ever.

6. Xender

Xender

Image Source:- hpssociety.info

Xender is one of the most useful android apps and a smart app that allows you to transfer files without any hassle right from the phone. This must have android app relieves you from carrying a flash drive or USB cable along to transfer the files as it does not require any connection with the PC to transmit or receive files.

Transferring files using Xender is a hassle-free and faster compared to Bluetooth and any other mode. This app is of a great help to those marketing professionals who have to keep sending important files back and forth via phones.

7. PicsArt

PicsArt

This is one of the most popular Android app and best Android app of all time which are amongst the most downloaded on the play store. It is one of the most loved photo editing apps for Android devices. The app is preloaded with numerous options for editing the pictures.

The app has allows you to share pictures right from the app to your social media accounts. One of the reasons why people prefer this app are its amazing features which include creating image collage, drawing on photo, frames, stickers, free cropping, mood changer tool. The app is absolutely free to a limited access with ads and then to access the premium features a minimal amount has to be paid.

8. Nova Launcher

Nova Launcher

Nova Launcher is one of the best launcher apps for android device for many years. The launcher is lightweight and easy to use with numerous customization options. A big bunch of launcher icons comes for free and from the play store to change the look and feel of using the mobile.

This app comes preloaded with app-drawer, scrollable dock, customizable icons, folders, notification badges with ample gestures for the ease of use. The app is absolutely free apart from the premium version that unlocks other features.

9. WhatsApp – Instant Messenger

WhatsApp

There are thousands of instant messaging app available in the market but the most favorite of all and the most downloaded messaging app on the Google play store is WhatsApp. This instant messaging app has become an integral part of everyone’s life nowadays and one cannot imagine a day without this.

The only basic requirement is internet and you get unlimited access to this instant messaging app. You can share pictures, videos, GIF’s, share contacts, share files and documents, create groups to share information, make voice and video calls and stay connected to the world. Not to forget WhatsApp is one of the secure Instant messaging App for both Android and IOS and one can use this app by using it even over a desktop.

10. LastPass

LastPass

How often do you forget your important login passwords? With everything being password protected for security reasons human minds have several passwords to remember and forgetting the password is very normal however retrieving them becomes a big task hence comes to your rescue LastPass an app that saves you from forgetting the important passwords of your various accounts, devices, and logins.

This app further helps you to lock down your password with all the personal information at a central location which is accessible only to you. The app is smart enough to autofill details in browsers and apps wherever required hence eliminates your task of going back and forth on the phone.

You have the facility to sync your password and data across all your devices hence making it easy for you to access it from anywhere. Moreover, this app works flawlessly across numerous platforms as compared and amongst the other latest apps for android phones.

Key Takeaways

This was the list of some of the best free android apps ever that can be utilized for day to day and other important usages. Now a day’s most of the Google apps are pre-loaded in the phone when you buy a new android phone.

However, the apps that are not there can be easily downloaded through the Google Play Store. The apps that we have listed are some of the musts and should have apps for all the smartphone users.

What do you feel about our compilation of the best ten free Android apps, we would like to hear your feedback in the comment section.

Written By : Technostacks