Firstly, Machine learning as well as artificial intelligence-based projects are obviously things that point out what the future holds. We want better personalization, smarter recommendations, as well as improved search functionality. Our apps should be able to see, hear, and respond – that’s what artificial intelligence (AI) has brought to the world, enhancing the user experience as well as creating value across many industries.

Particularly, Now you likely to face two major questions: How can I bring these experiences to life? and What programming language is used for AI and ML? You should consider using Python for AI and machine learning.
 

What makes Python the best programming language for both machine learning as well as AI applications?

Particularly, When the question is about AI, its projects differ from traditional software projects. Firstly, the differences lie in the technology stack that is being used, the skills that are required for an AI-based project, as well as the ability or the necessity of deep research. In order to implement your AI aspirations, you should consider making use of a programming language that is stable, flexible, as well as has all the tools available. Python offers all of this to the developers and programmers, which is why we see lots of Python AI projects today thus making it apt for the best fit.

From development to deployment as well as maintenance, Python helps developers and programmers be productive and confident about the software that they’re building and making. Benefits that make Python the best fit for machine learning and AI-based projects are simply abundant. These benefits include simplicity and consistency, access to great libraries and frameworks for AI and machine learning (ML), flexibility, platform independence, and a wide community. These are going to add to the overall popularity of the language.

Simple and consistent:

in Conclusion, Python offers concise and easily understandable and readable code. While there are complex algorithms and versatile workflows that stand behind machine learning and AI, Python’s simplicity and easy to understand code allows developers and programmers to write reliable systems. Developers are able to get together and put all their effort into solving an ML problem instead of focusing on the technical nuances of the language.

Additionally, Python is appealing to many programmers and developers as it’s easy to learn. Python code is understandable by humans just as plain English, which makes it easier to build models for machine learning.

Many programmers say that Python is going to be much more intuitive than other programming languages. Others point out the many frameworks, libraries, as well as extensions that simplify the implementation of different Python-based functionalities. It’s generally accepted and acknowledged that Python is suitable for collaborative implementation. When the need stand to use multiple developers, python support comes first. Since Python is a general-purpose language that can be used for almost anything, it can do a set of complex machine learning tasks and enable developers and programmers to build prototypes quickly. This in turn allows you to test your product for machine learning purposes.
 

An extensive selection of libraries and frameworks:

Implementing AI and ML algorithms can be sometimes or at times be tricky and require a lot of time. It’s vital to have a well-structured as well as a compatible and well-tested environment to enable developers to come up with the best coding solutions.

In order to reduce development time, programmers turn to a number of Python frameworks and libraries. A software library is nothing but a pre-written code that developers and programmers use to solve common programming tasks. Python, with its rich technology stack, has an extensive set of libraries that is used for artificial intelligence and machine learning. Here are some of them:

• • Keras, TensorFlow, and Scikit-learn for machine learning
  • NumPy for high-performance scientific computing as well as for data analysis
  • SciPy  used for advanced computing
  • Pandas for general-purpose data analysis
  • Seaborn for data visualization

Scikit-learn features have been including various classification, regression, and clustering algorithms, these include support vector machines, random forests, gradient boosting, k-means, and also DBSCAN. These features are designed to work with the Python numerical and scientific libraries NumPy and SciPy.

With these solutions, you can develop and create your product faster. Your development team won’t have to reinvent the wheel. You can make use an existing library to implement necessary features.

Also Read: How AI and ML have Revamped Mobile App Development Industry

What is Python good for?- Python for Artificial intelligence and Machine Learning

Here’s a table of сommon AI use cases and technologies that are best suited for them. We recommend using these:

Platform independence:

Platform independence has always referred to a programming language or framework that allows developers and programmers to implement things on one machine and use them on another machine without any (or with only minimal) changes. One key to Python’s popularity is that it is a platform-independent language. Python provides and enables supports for many platforms including Linux, Windows, and macOS.

What’s more, developers and programmers usually use services such as Google or Amazon for their computing needs. However, you can often find companies and data scientists who use their own machines that has powerful Graphics Processing Units (GPUs) in order to train their ML models. And the fact that Python has always been platform independent, this makes training a lot cheaper and easier.
 

Great community and popularity:

In the Developer Survey 2018 by Stack Overflow, Python was among the top 10 most popular programming languages, which ultimately means that you can find a development company with the necessary skill set to build your AI-based project.

Recommended Read: Difference Between Artificial Intelligence And Machine Learning

Conclusion

So you see these are the major reasons why Python is the most preferred language as far as AI and ML are concerned. Pythons increasing popularity is key to using it for different ML and AI applications. Hope you like this blog on Why Use Python for Artificial intelligence and Machine Learning? If you are looking to Hire Python Developer then do mail us on enquiry@nimapinfotech.com

Overview- Django vs Spring

Every once in a while a technology comes that changes the playground. Firstly, Developers benefit from the emergence of these technologies as it helps in programming and designing.  In the world of web technologies, there have been constant improvements that help designers and developers. Secondly, These improvements help developers create awesome applications and websites. Particularly, there has been an explosion where there are different technologies. In short, these can be mixed and matched to create the desired applications.

In this article, we are going to have a look at two of the web technologies that help to create these applications. These are Django and Spring.

Features Comparison

Django as well as spring can be primarily classified as Full Stack framework tools.

“Django is the web framework that adheres to deadlines.” These are the statements from an experienced Django developer. The Django framework is a python based framework that provides developers with clean and pragmatic design. Django is a more mature framework than Spring. When the developers consider Django as their primary development technology, they are able to get rapid action development, Great community, as well as open source features.

Let’s discuss somethings about Spring:

In our comparison of Django VS Spring, we have come up with the following points.

Spring is a Java-based programming and configuration model framework.  This framework is used for  Java based enterprise applications. One of the prima-facie elements of Spring is that it provides infrastructural support at the application level. Spring provides a focus on the plumbing of enterprise applications. When Spring is used teams are able to focus on application business logic. The development team does not have unnecessary dependencies on specific development environments. When the developers consider spring then they can gain Open source features, Great community support as well as Java features. Spring is a strongly typed language. Spring does not have powerful and thorough documentation as offered by Django.

Django as well as spring are both open-source tools frameworks that helps developers build excellent applications. These applications can both be web-based as well as standalone. Django being a more mature language has more Github stars and forks compared to spring. Companies prefer Django more than Spring. This is evident as Django has been featured in 979 stacks and 882 developer stacks as quoted by StackShare. Django is not a strongly-typed, or it is a loosely typed language.

Let’s have a detailed comparison of these two technologies: Django vs Spring.

Side by side Detailed comparison. Django vs Spring

Conclusion:

In conclusion, each language has its own sets of pros and cons. Particularly, We have listed to you the various differences as well as the similarities of each language. It comes down to personal preference which language does developers want to use. It comes down to the features that developers want their applications to have. If you liked this Django vs Spring article and want to hire Django developers or hire spring developers then do contact us at enquiry@nimapinfotech.com with your requirements. We have talented and experienced developers ready to onboard your project with full customer satisfaction guarantee.

Firstly, Python is an interpreted high-level programming language with dynamic semantics and object-oriented programming designed to be easy to read and implement. It is a scripting language like Perl/ruby and used for creating web applications too. Java-Script is an object-oriented programming language which allows you to create dynamic web pages and got standardized in ECMAScript language specification. Java-Script supports different programming paradigm as object-oriented, functional, and imperative programming but not procedural programming.

What is Python?

Particularly, Python supports different programming paradigm as object-oriented programming, functional programming, imperative programming, and procedural programming. It came up with huge built-in modules and packages. It allows programmers to use different program styles for simple and complex programs.  now we will discuss the Python vs Javascript.

What is Java-Script?

Secondly, Java-Script is an object-oriented programming language. It is highly used in browsers to provide dynamic functionality which we cannot achieve through normal HTML and CSS. It has support for standard applications with text, regular expressions, and dates.

Lets us start with the comparison: Python vs JavaScript

Direct Comparison

Key Differences between Python and JavaScript

In summary, lets us see some of the points that shows the Differences Between Python vs JavaScript

• Python is strongly typed – no implicit conversion between types whereas JavaScript is weakly typed.
• The synchronous and blocking code is standard in JavaScript whereas python as de-facto as default.
• JavaScript can be used to run on frontend whereas python is on server side programming or backend.
• Python has procedural programming whereas Java-Script does not have.
• Java-Script has; as statement terminator whereas python has a newline.
• Python is a better-designed language which makes it easy to maintain whereas JavaScript is poor.
• Python is not good for mobile development whereas Java-Script is good.
• Python is slow to run comparatively to JavaScript.
• Python provides huge standard library whereas JavaScript has a limited standard library.
• Python heavily relies on assignment with no difference between variable and assignment whereas JavaScript doesn’t relay.
• Python has many libraries for scientific computing, data analytics, and machine learning whereas JavaScript does not.

Recommended Read: Laravel VS Python VS NodeJS

• Python has support for many numeral data types like int, float, fixed-point decimal whereas Java-Script mainly works on floating point variables.
• Python has inbuilt REPL whereas JavaScript does not have.
• JavaScript runs on both browser and server whereas python is mostly used for server-side programming.
• Python is easy to get started comparatively to JavaScript.
• Python is easy to find new jobs comparatively to JavaScript in this year.
• Python object-based is nearly equal to JavaScript and python supports programming style which uses simple functions and variables.
• JavaScript is most complex modern programming language comparatively to python.
• Python and JavaScript both use a lexical scope with small differences.
• Python has a Self-argument as the first argument for each method whereas JavaScript has accessed the object using “this”.
• Unlike JavaScript, python does not have a way to inherit from instances.
• Python is good if we do data analytics, machine learning or math-intensive operations whereas JavaScript is good for building a website or native applications as it took less time for UI work.

Also Read: PHP vs Python

Firstly, for any kind of web development, as a web developer its better to go with PHP and Laravel over Python and Django. But they’re both great pairings of powerful tools with long futures. Let’s get into the pluses and minuses.

In summary, if you compare the two language wise, PHP is a language designed for the web. It’s made from the ground up specifically for web development and the fastest development language in that environment. PHP 7 also seems to be much more efficient than Python 3. It needs less VPS memory overhead in order to achieve and accomplish the same task. As long as we’re talking about web tasks. (PHP is more performant though, Laravel does not necessarily share that performance.)

Convenience for Web development

Python 3, on the other hand, is useful to know far beyond the web development spectrum.  If you are also into other things. Much like C# is known as the language for modern video game development. Or any kind of cross-platform mobile development. Python is known increasingly as the language for Big Data and AI.  It is also used for machine learning analysis and predictive analysis. the more you are going to use Python with Django, the better suited and abled you will be for these other useful areas in the near future.

There are going to be more web development jobs and tasks for PHP coders. But there are more jobs in general for Python coders as well. It depends on how dedicated you are to the web, as most PHP jobs or gigs will be related to WordPress or, increasingly now, Laravel. PHP is all web designing and development, all the time.

Framework-wise, Laravel also makes you and enables the use of classic, traditional OOPs (object-oriented programming) as well as the MVC (model-view-controller) patterns. You will be very ready to use other robust and solid MVC frameworks. Examples  (like say .NET) after mastering and gaining insights for Laravel. Django is less so, as it’s a little more quirky as well as unique with its MVT patttern (model-view-template) approach. It is a bit less married to the OOP paradigm per se.

Google Trends Comparison-

PHP with Laravel or Python with Django

Laravel also has gained a huge amount of considerable momentum over Django as of 2018. Let’s see the Google Trends results for how many people are seeking info on Laravel these days. How many (fewer) are checking out Django. I also used Ruby on Rails for good measure, which was #1 in this comparison.  It faired recently through 2013 and 2016 but is now #3 out of 3 as of 2018.

Laravel first passed over the Django framework overall in developer “interest” two years ago in April 2016, then passed Ruby on Rails in December 2016, and has gradually increased its lead over both the frameworks through every month of 2017 and, so far, and as of 2018. There is actually a bit lesser new interest in Django or Rails today than there was over five years ago on May 1, 2013. Meanwhile, if you see there exists a 700% more interest in Laravel today than there was on May 1, 2013.
The math is coming up Laravel.

Recommended Read: PHP vs Python

You can not really go wrong with either of these frameworks, but if you are equally proficient and have mastered PHP and Python, Laravel has the momentum as well as the stricter (or at least more traditional) adherence to certain “best practices” that exists in the field of web programmings such as OOPs and MVC. And, language-wise, PHP powers much of the websites that are out there.,(thanks in part to WordPress) and there will undoubtedly be plenty of such kind of open opportunities in PHP web development for decades into the future.

Primarily for the above listed three reasons, Laravel and PHP are probably going to be your best bets for web development as of 2018 and looking toward the 2020s.

Frameworks Popularity

We are also adding the caveat that we saw on TechEmpower.If you compare this with raw PHP, you will find that Laravel does not perform better. For a basic web app that is going to have hundreds of users, Laravel is a joy to use. But for something much larger and scalable, an upgrade to the similar (by way of MVC and OOP) yet slightly more complex .NET Framework may be in your future.

If you are building a really large or high traffic website that has tens of thousands of users, I’d maybe consider Django for the job after all, or more likely make the use of ASP.net Core 2 or Node.js instead of either. That being said, Laravel is able to handle whatever you’d throw at it. You’d just need to upgrade the hardware. We can also have expectations that Laravel will make performance improvements, as it’s still relatively new compared to each of these much more mature frameworks.

Also Read: Django vs Laravel: Which Web Application Framework to Choose?

If you are looking to build your website, web application or mobile application with PHP with Laravel or Python with Django or want to hire developers then contact us on enquiry@nimapinfotech.com

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Overview- Laravel vs Python vs NodeJS

Often at times there are invention of a particular programming environment or language that changes the game. These inventions are boon towards ushering a new era or generation in computing and programming. We have been able to solve common problems that comes across computing using these newer languages and techniques. These languages make somethings possible that otherwise seemed to a dream. We are going to look at 3 particular languages and platforms that helps mankind. We will compare and contrast 3 languages that are popular: NodeJS, Laravel and Python.

Have you been a programmer or are looking to becoming a programmer. You need to have an eye for the latest trends and updates that are taking place in the IT industry. Did You know that there are about 600 programming languages and this list is constantly increasing day by day?

It is very crucial for any programmer to know the basics of any programming language as well as they should have in-depth knowledge of the programming languages that they are going to use in order to expand their programming careers.

It has been very important to learn newer languages and frameworks in order to stay relevant and updated in the market. This knowledge will ensure that they can grow their careers with the in-demand rising newer languages and frameworks.

Popular demand of languages

There can be several reasons why clients and customers want their projects to be developed in big, popular, and the latest languages. But how can one analyze whether a particular language is in demand or not? Every language has a set purpose and a reason for a job demand for that language.

These languages can be popular for seemingly a wide variety of reasons. These languages provide programmers and developers with the features that was non existent in other older languages.

In order to choose the right language for up-gradation of your knowledge and your skillets, you need to have a basic understanding of the languages. This knowledge will enable you to make informed decisions as well researched choices

Let’s compare and contrast 3 of the most popular programming languages and frameworks that are highly in demand for today’s computational era. (Laravel vs Python vs NodeJS)

Laravel:

It is one of the popular PHP based frameworks. This is a new generation web application framework that is used to design web applications. Laravel has an expressive and elegant syntax representation that encourages less code writing thus reducing the possibility for errors to creep inside the developer’s code.

It makes the entire process of coding a lot easier and fun to perform. This makes development creative and enjoyable. The main purpose of this framework is to ease common tasks that are done by developers as well as reduce the pain points that are faced by developers.

This open-source framework also provides powerful tools for developers that are easily accessible. This framework is capable of easing the tasks such as routing, caching, authentication and sessions that are commonly performed tasks in web-based projects. Laravel also provides a high level of abstraction as well as clear conventions for any kind of logical problem-solving tasks.

Laravel has been quite famous with businesses and developers due to its vast amount of features that it offers. The newer version of laravel already has simplified methods of injection. This web framework is able to cover the needs of small as well as large enterprises. Being a feature-packed platform that offers new capabilities to web developers, it also provides stronger community support in order to resolve any programming issues

List of Features offered by Laravel:

Laravel provides extensive support for MVC architecture,
It provides strong security for web applications.
Gives the facility of providing the Bcrypt Hashing algorithm in order to generate encrypted passwords.
It provides programmers with built-in lightweight templates as well as dynamic content seeding in order to create layouts
It provides the option to write SQL queries in PHP using Object Relational Mapping
Eases and facilitates easy unit testing for developers.

Python:

Python is a high-level cross-platform language. It is an object-oriented, interactive as well as interpreted scripting language that is highly readable. The best part of this language is its ability to use English words frequently in code.

If you are starting new and is a beginner in programming then Python is the best language to start with. The syntactical simplicity that this platform provides allows beginners to perform high levels of coding very easily.

Python is an integrated language which means that the code is interpreted line by line during the execution. Developers have no need to learn a specific editor, build a system or develop an integrated development environment in order to use this platform.

Python can be used for a huge and wide range of applications right from the game to internet browser development. It is an ideal language for ad-hoc programming which has been popular nowadays as it also can be used for prototype development. It is a core language that is used for scientific computing, data mining as well as for machine learning.

List of features offered by Python:

Debugging is made easy due to the interpretive nature of the language

It is an open-source and a free language that has the source code freely available

It fully supports the object-oriented concepts of objects and classes.

Python can be easily integrated with other languages

It can run on many platforms equally such as Mac, Unix, Linux, and Windows

You may also like to know more: Codeigniter or Laravel?

Node JS

Node JS is an open-source and cross-platform runtime environment, it is built on the V8 JavaScript engine by Chrome. It enables major users of JavaScript in order to perform server-side scripting and also run scripts to produce web content dynamically.

It is not like a traditional programming language and its execution is quite different. NodeJS packs more of a run time environment and it makes use of an event-driven model that uses a non-blocking I/o model architecture.

This runtime environment was first introduced by Ryan Dahl in 2009, slowly this environment has developed support for Mac OS and Linux. The support for the Windows Operating system was introduced in 2011, Node JS is scalable, lightweight as well as efficient.

Node JS is useful and easily learned by both backend and front end developers.

List of features offered by NodeJS

NodeJS is single-threaded hence it supports thousands of concurrent connections

NodeJS provides a unified API that allows being combined with JSON data, browser and more

Provides an asynchronous library that is full of features

It is highly scalable to many requests

Applications written in NodeJS outputs the processed data in chunks and hence there is no buffering involved
Code execution is very fast.

It is well instrumented for production usage

It is versatile and is being used for a wide range of exhaustive lists of applications, projects, and companies.

Recommended Reading: Pros and Cons of Laravel

Conclusion:

So we have seen the various benefits and features offered by these platforms Laravel vs Python vs NodeJS. It is evident that every platform has its own pros and cons and it depends on the companies or client requirements to choose a particular programming language or platform depending on the features and benefits that are offered.

If you’re looking to hire Laravel developers or hire python developers or hire node js developers then do contact us with your requirements, and we will help you develop your project