Python vs Java: How Do They Compare?

When it comes to programming and coding, the programming language only plays half the role. Most of the heavyweight work is done by the ability of the coder to think on his toes – irrespective of the language. Having said that, it’s still a pickle of a situation if you’re new to the world of programming but know little about the differences in various programming languages. Today, we’ll look at a comparison between two of the most popular languages among developers far and wide – Java and Python,

Both these programming languages have their similarities and unique features that set them apart. The most striking similarity between Python and Java is their “object-oriented” design. However, they have prominent differences too.

Let’s us take a closer look at the areas where Python and Java differ from each other.

Dynamic vs. Static Typing

The key difference between Python and Java is that while the former is dynamically typed, the latter is statically typed.

When we say that Python is dynamically typed, we mean to say Python allows you to alter the type of variables used. For instance, you can replace an integer in your code with a string. However, you need to ensure that the object that a name refers to supports the operations necessary for running that particular object instances in the code. For example, a code may have two types of object – Cat, and Dog. While Cat and Dog may both support the operation “run,” Dog also corresponds to “friend.” As long as the code only refers to the common operation“ run,” it won’t matter if it pertains to Cat or Dog. This is known as “Duck Typing.”

Contrary to this, Java requires you to strictly define the type of a variable the instant you first feed it in the code. You cannot change the variable type later in the program. This is known as static typing.

While many coders argue that dynamic typing is convenient and more comfortable to work with, others would argue that static typing helps reduce the risk of undetected errors in the code.

Indentation vs. Braces

Like most programming languages, Java uses curly braces to define the beginning and end of every function and class in the code. Python, on the other hand, uses indentation to segregate the code into blocks. An advantage of indentation is that it allows you to build your program in a way that’s easier to read and understand. Also, there remains no possibility of errors in the code due to missing braces. However, while working with Python, you need to make sure to end the indentation with a colon.

Compatibility vs. Speed

When it comes to portability and compatibility, Java has the upper hand over Python – it can be used to design platform-independent apps. If any device (PC or mobile) can run JVM, it can support Java applications without any hassle. Considering how popular Java is for web apps and desktop programs, it can be safely assumed that most devices are JVM integrated. Hence, they can run any Java program efficiently. Contrary to this, to run Python programs, you need a compiler to convert the Python code into the version that’s compatible with your operating system. However, when a Java code runs on JVM, it usually runs slower than Python codes.

When these features are compared, Python would be recommended by most programmers as the easier language of the two, ideal for rookies. However, Java holds a prominent place among programming languages and is widely used for developing Android apps and web apps. So, no matter which language you choose, you need to remember that programming is fundamentally about logic. It is about building your computational skills. The key is to be versatile. When you master one programming language and have the basic understanding of programming concepts, you can effortlessly switch to any other programming language.

All of these differences will help you in choosing a language to begin with. But, like we said earlier, at the end of the day, it’s all about logical reasoning and the ability to think on your toes. And we’re here exactly for that. Drop by at Coding Ninjas and set your first steps right. We help you develop the required knowledge to tackle any programming language.

PS: There are also early bird discounts! Come on in, quick!

5 essential tools for front-end web development:

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If you just decided to continue reading what’s under this headline, then you must be having basic knowledge of HTML and CSS. If you don’t, though, don’t fret too much. Keep this tab open, and read our article on building your first HTML page. You’ll be good to go.

However, the world of front-end web development is extremely wide and goes beyond just notepad or a simple text editor. Let’s look at five essential tools that must be in your toolkit to help you better:

Sublime Text:

Sublime is a sophisticated, cross-platform text editor, found invaluable to its users. It provides quick navigation to files, instant jumps to symbols and allows moving around lines of text very quickly with only a few keystrokes. It eases writing the code by allowing multiple selections for manipulating the lines of text. Its ‘Split Editing’ feature edits multiple files side by side, saving time to its best. This editor offers power tools for code indentation and everything in Sublime Text is customizable with the help of simple JSON files. It is a project-specific editor which allows you to switch between projects instantly. With its numerous useful features and unmatched responsiveness, Sublime Text sets the bar for performance.

Bootstrap:

Bootstrap is a flexible, open source, HTML, CSS, and JavaScript framework for faster and easier web development. It offers ready-made blocks of code that are free to use and save a lot of time as there is no need of writing code from scratch. It follows Mobile First Approach and is used for creating responsive web design where the layout of the page is dynamically adjustable according to the specifications of the devices it is viewed on. It is highly customizable and provides cross-browser compatibility.

Sass:

Sass (Syntactically Awesome Style Sheets) is a preprocessor scripting language used to write code which is compiled into Cascading Style Sheets, CSS. One should think of Sass as “CSS with superpowers” because of its various added advantages, one of them being the high degree of code reusability that it offers. Code reusability is performed via ‘sass variables’ and ‘mixins’. Mixins are used to group CSS descriptions and reuse them wherever required throughout the file. Sass breaks down the complex code into small code snippets, making the CSS even more modular and less complicated. It allows nesting in coding, making development a more pleasant experience.

React:

React is the JavaScript library which is used in the development of the single-page applications. This toolkit follows the component-centric approach, i.e., it breaks apart the large complex user interface into small components which can be used for every web developer. We use React to describe the Web User Interfaces. We tell it what do we need in our User Interface, and it translates our declarative description into actual user interfaces in the browser. React uses Virtual Document Object Model (Virtual DOM). It gives a virtual representation of the updates if the entire page is rendered on each change, while changes are only rendered in the subcomponents that change. The motive of the React library is to provide speed, scalability, and simplicity to the web developers for better designing at the front-end.

Git:

Git is a version control system, or you can think of it as the software used by the web developers to keep track of all the activities involved in their project. As Git maintains a complete history of all the changes made in all the web files, you can go back and restore all the details of any version. If you’re continually making changes in your HTML, CSS or any other data, and you want to back up every version of every changed file in your project, Git is strongly recommended for you.  
Our specialized course on web-development takes you through the world of HTML, CSS, JavaScript, Ruby, and a lot more. Get yourself enrolled ASAP and build an awesome web-app for yourself!

Choosing Your Java IDE

IDE that is, Integrated Development Environment is an essential tool for every programmer using Java. IDEs are heavily feature-oriented and hence, make Java programming much more convenient and constructive. Although there are many IDEs that are used by programmers and coders across the world, the three most preferred IDEs for Java are Eclipse, NetBeans, and IntelliJ IDEA.

Choosing the right Java IDE depends on factors such as the nature of your project, your level of programming skills, and the process used by your development team. Whatever Java IDE you choose, it should allow you to freely edit, develop, debug, and test your systems, so that apart from a well-crafted code, you also have intelligent refactoring and code metrics.

So, let’s delve into the Java IDEs and know which serves what purpose!

Eclipse

Eclipse is a free open-source IDE that has long been one of the most popular IDE for writing in Java. Launched in 2001, Eclipse was a project of IBM developed to replace the Smalltalk-based IBM Visual Age family of IDEs. It is compatible with Windows, Oracle Solaris, Linux, and Mac OS X.

One of the most exceptional features of Eclipse is that it has a plugin design that allows it to be extended to other languages as well. These plugins support nearly hundred programming languages and over 200 application development frameworks. Another good thing about Eclipse IDE is that a project designed using this displays a model of its contents including the declaration of Java elements and the details about the type hierarchy along with references. The debug support feature of Eclipse runs both locally and remotely provided you use a JVM that supports remote debugging.  

Eclipse is primarily used for developing web, enterprise, desktop, and mobile applications.  

NetBeans

Initially launched as a commercial product in 1997, NetBeans IDE was bought by Sun Microsystems in 1999 and was released as an open-source IDE in 2000. The present version of NetBeans (8.1) is compatible with Linux, Windows, Mac OS X, and Solaris.

Although NetBeans has fewer plugins than Eclipse, Oracle still considers it as the official IDE for Java 8. It offers great support for Java 8 as well as for the conversion of older codes. The editor, code analyzer, and converter tools of NetBeans allow programmers to upgrade applications to be compatible with new Java 8 language constructs (example: lambdas, functional operations, and method references). The end-to-end development design of NetBeans provides a convenient environment for secure and easy coding, testing, debugging, compiling, profiling, analysis, and deployment.  

NetBeans’ language-aware tool detects errors in real-time while you are writing your code and provides you with useful documentation popups and smart code completion ideas. The Inspect & Transform tool of NetBeans allows programmers to inspect their codebase, while automatically fixing the errors in the code. Furthermore, NetBeans has a variety of refactoring tools using which you can analyze your code and restructure the code without breaking it.

IntelliJ IDEA

IntelliJ IDEA is the premium Java IDE that comes in two editions: free Community edition and the paid Ultimate edition. It was developed by JetBrains. While the Community edition is suited for JVM and Android development, the Ultimate version with additional features is designed to support web and enterprise development.

The Community version supports Java, Kotlin, Groovy, Scala, Maven, Gradle, SBT, SVN, Mercurial, and CVS. On the other hand, the Ultimate version supports Perforce, ClearCase, TFS, Git, SVN, Mercurial, CVS, JavaScript, and TypeScript. Some of the most helpful additional features of Ultimate edition are:

  • Spring MVC framework, Spring Integration, Spring Boot, and Spring Security.
  • Support frameworks like Node.js, Angular, and React.
  • Java EE support such as JSF, JAX-RS, JPA, CDI.

The most striking feature of IntelliJ is IDEA that is designed to provide an in-depth insight into your code with the help of developer ergonomics, built-in developer tools, and polyglot programming experience. IDEA offers “smart completion” of code by listing pop-ups of most relevant symbols best suited for your current code context.

Apart from these three IDE, there are also various lightweight IDEs available such as DrJava, BlueJ, JCreator, and Eclipse Che. Every IDE has its distinctive features, functions, and benefits. But, to fully utilize the features of any of these IDEs, you need to have a strong grip on the concepts of Java.

So, don’t wait any longer – hop on to Coding Ninjas where we cover the fundamentals of Java programming language in our online as well as offline courses. Oh, and if you’re confused as to which course to choose – online or offline, we recommend you read our article on the same.

Programming Languages That Will Rule The World In 2018

programming-languages-that-rule-the-world-18

The ever-changing arena of software development has given rise to numerous advanced programming languages that are encouraging smart programming with minimal bugs. Ever since the invention of the binary, programming languages have continued to evolve at a rapid pace, so much so that now we even have software that can interact with us just like another human being (Siri, Alexa)!

Over time, newer and better programming languages take over outdated programming languages, transforming the way we feed instructions to computers. As of 2018, these are going to be the hottest programming languages in software tech.

JavaScript

Over the years, JavaScript has continued to hold one of the top positions in programming languages across the world. And it looks like it’s not going to fade away anytime soon. The surge in the number of mobile users and consequent rise in the demand for web apps has increased the need for JavaScript and other JS-based frameworks such as React, Angular 5, and VUE.

Today, JavaScript has found its applications almost everywhere in the software sector, from front-end development to web app development. And it is the secret behind some of the most well-designed pages on the web. In a survey conducted by StackOverflow, it was found that nearly 85% of developers use JavaScript.

Swift

2014 saw the release of Swift by Apple. When Apple realized that coding in Objective C is quite frustrating, they saw an opportunity to bring in a new, and better programming language into the scene.

The language specification of Swift is comprehensive with many new features. With Swift, one can create high-quality, seamless, and stable applications. Also, Apple strongly relies on Swift while designing OS X  and iOS apps and, given the simplicity of the language (easy to understand and work with), it can be safely concluded that Swift might just become one of the key programming languages in the upcoming 20 years.

Python

Python is a high-level programming language – an amalgamation of the best features of C and C++. What makes Python so amazing is the auto memory management coupled with its function and object-oriented functionality. It is highly dynamic and readable.

Python is used in web development, in designing GUIs (Graphic User Interfaces) such as video games, and a host of applications (audio/video, console, administration, etc.). Most of you are familiar with Instagram, YouTube, and Reddit. Wonder how they’re so smooth and well-crafted? Well, it’s Python guys!

Scala

If you’re into functional programming, Scala is the perfect programming language for you! Loaded with some fantastic features such as flexibility, scalability, real-time processing powers, and object-oriented nature, Scala has emerged to become a popular choice among software developers.

Since Scala was designed to run on JVM, so anything you code with Scala can run anywhere that is Java friendly! It is most widely used to develop web apps, Ad hoc scripting in REPL, and analyze data with Spark, to name a few.

R

Being a free open-source statistical programming language, R is currently the most favorite programming language of statisticians and data miners. Using the power of statistics, R can reveal patterns even in large datasets. The most commendable trait of R has to be its ability to solve complex problems.

R is in high demand among data scientists since it comes equipped with the fundamental functions necessary for data analysis along with some of the most useful statistical algorithms that are the requisites of data-driven science.

So, which among these are you planning to take up? Don’t think too much, pick a language, visit Coding Ninjas, get yourself enrolled in one of our courses, and see yourself sail through!

Must know questions for the Android developer interview

must-known-questions-for-android-dev-interview

In this ever-augmenting world of technology, the smartphones have become a primary entity for the people to survive. As you know, Android is the most feasible and commonly used operating system for mobiles, and the need, scope, and value of the Android Developers are only increasing in the market.

If you have an interview around the corner, we recommend you go through this list of 12 essential interview questions. Also, even if you don’t have an interview, it’s still recommended to go through them – a little revision never hurts!

  1. Describe the components of an Android Application Architecture.

Android Application Architecture has the following components:

Services: Services run in the background. For example, the facebook notifications, they continue to run, even if you switch the application.

Intent: It forms the interconnection between activities(actions performed on the screen) and the data passing mechanism by passing messages as per the request actions.

Resource Externalization: Externalization of resources is done for the ease to maintain, update and manage the resources.

Notification: It includes light, sound, icon, notification dialog box and toast.

Content Providers: It enables data sharing across different applications with the help of a uniform interface to access the data.

  1. What is do you mean by an APK format?

Android application package (APK) is the package file format used to install application software and middleware onto an Android operating system.

  1. What is an Android Manifest File?

Every Android application must possess an AndroidManifest.xml file in its root directory. This file presents essential information about your app to the Android system that it must have before it can run any of the app’s code.

  1. What are the languages used for Android Application Development?

The android application development is written in Java(Android SDK) and C/C++(Android NDK).

  1. What does ADT stand for?

ADT stands for Android Development Tool. It is used to develop and test the android applications.

  1. What does ANR stand for?

ANR is a dialog box that appears when an application is not responding. It stands for “application not responding”.

  1. What do you mean by ADB in Android?

Android Debug Bridge is a command line utility in Android SDK which lets the system communicate with a device. It can be used to control your device over USB from a computer, to copy files, install and uninstall apps, run shell commands, etc.

  1. What are the key components of the Android Architecture?
  • Libraries
  • Linux Kernel
  • Android Framework
  • Android applications
  1. What is an AdapterView in Android?

An AdapterView is a group of widgets in Android which includes the ListView, GridView, and Spinner. It also provides the layout of the underlying data for the view.

  1. What do you mean by a Container in Android?

The container is a description of the views which holds the dynamic content. It is used to hold objects,widgets,labels,fields,icons,buttons.etc.

  1. What are the notifications available in Android?
  • Toast Notification: It shows a pop-up message on the surface of the window.
  • Status Bar Notification: It shows the notification on the Status Bar.
  • Dialogue Notification: This type of notification is activity related.
  1. What are the tools available in an Android SDK? Describe them.
  • Android: This tool allows you to manage the projects, AVDs and the components installed in the SDK.
  • ddms: It is used to debug Android applications.
  • Emulator: It is used to test the applications without using any physical device.
  • Draw 9-Patch: It is used to create a NinePatch graphic with the help of a WYSIWYG editor.
  • mksdcard: It is used to create a disk image that you can use with the emulator.
  • Sqlite3: This tool lets you access the SQLite files that are created and used by the Android applications
  • Proguard: This tool is used to shrink, optimize, and obfuscate your code by removing the unused code.
  • Traceview: It provides a graphical viewer to view the application logs in your application.
  • Adb: Adb stands for Android Debug Bridge. It is a versatile command line tool that helps you communicate with a device.

These questions skim through the basics of android app development, and the answers to these questions are a must know for anyone aiming for an android developer role. If you had any problems understanding any of these questions/answers, we recommend you drop by at Coding Ninjas. We have specially curated courses on Android App Development that’ll help you sail through the Android world with ease. 

Things To Know Before Building Your First Android Application

things-to-know-before-building-android-application

With the advent of smartphones, the number of mobile users across the world has been rising exponentially over the years. As we continue to become increasingly dependent on mobile applications for fulfilling many of our needs, the world of mobile apps is also steadily expanding. As of 2015, the number of mobile users globally was 4.43 billion, and by 2019, this figure is expected to hit 5.07 billion. Today, there are almost 1.6 million Android apps in Google Play Store and nearly 1.5 million iOS apps in the Apple App Store.

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Such increasing numbers of mobile users and applications show that it’s a booming opportunity for app developers now! However, if you think that having a great idea for an app is the only thing you need to launch your first Android app, you are mistaken. There are a few things you need to know before leaping into the world of Android applications.

Let us now look at the MOST important things you need to know before building your first Android app.

  1. Learning to Code

When you are keen to develop Android apps, you have to learn how to code. And to code, you need to have an in-depth knowledge of Java. It is a must. You have to start with the basics of app development and for this, you could either enroll yourself in online coding courses or browse through educational tutorials across YouTube, Google, and Bing. In case you want a more professional guidance to coding, try out the online coding courses by Coding Ninjas.

Another crucial thing you need to learn is XML. XML plays a big part in app design and development and learning it along with coding is a wise idea. And if you can, get your hands on this gem – Android Programming: The Big Nerd Ranch Guide.

  1. Get Familiar With IDE

IDE or Integrated Development Environment provides you with the user interface where you can enter your code. Unlike softwares that require you to write two separate codes (one for compilation and one for running), IDEs let you compile and run the code simultaneously. They also allow programmers to test apps in an emulation environment that helps highlight errors and issues in the coding syntax, it also isolates and fixes bugs through debugging. The most popular IDE choice for Android is Android Studio (powered by Google) and Eclipse. However, while Android Studio is exclusively designed for Android app development, Eclipse is a much more generalized IDE.

Some amazing features of Android Studio are:

  • Gradle Integration
  • Advanced Code Completion
  • Fantastic User Interface
  • System Stability
  • Drag and Drop tool

Apart from IDE, app developers can also opt for Android SDK (Software Development Kit) that comprises of debugger, emulator, documentation, libraries, sample code, and tutorials. These tools will help you work on the glitches of your app and improve it.

  1. Don’t Hesitate To Rely On Expert Help

Being a rookie, there will be times when you find yourself stuck on some problem or the other. There are many free online tools such as Stack Overflow, that’ll help you wiggle through such tricky situations in no time. And for everything else, there’s always Google!

  1. Do Your Homework – Market Research

In-Depth market research is essential when you are developing an Android app. Market analyzations can provide you with valuable insights about your potential competitors, your target audience, and the kind of app that is demanded by your target audience. Knowing these key information pieces will allow you to understand the pain points of the mobile demographic and develop your app in a way that it can resolve those pain points seamlessly, enhancing the overall customer service experience.  
At Coding Ninjas, we take care of everything you need to know before, during, and after building an android application. Our expert instructors combined with an unmatched curriculum is what you should be looking for, if android app development is on your cards. Drop by at Coding Ninjas and have a look at a vast catalogue of courses and pick the one you like best!

How Is Machine Learning Transforming The World Today?

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Technology is rapidly transforming our world today. Smart and intelligent devices and machines have made our lives much more convenient and comfortable. And the driving factor behind this is Big Data. IBM maintains that 90% of the data that we have at our disposal today has been generated only in last two years! So one can only begin to imagine the extent of massive amounts of data being generated across the world every day, and it is bound to increase in the near future. And to process and analyze all this data into valuable information, we need Machine Learning and Artificial Intelligence.

Machine Learning (ML) is a tool of digital revolution aiming to transform the present computing processes into more efficient, accurate, and cost-effective ones. ML is a branch of computer science that automates analytical model building. The concept of ML is based on creating such systems that could learn from data and identify the data patterns to aid in the decision-making process. In 2015, Gartner published a report stating that over 75% of companies are investing in Big Data.

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Source

This graph indicates the share of 2017 IT budgets that were earmarked for machine learning among adopters of machine learning worldwide (as of late 2016).

How Can ML Solve Our Problems?

Machine Learning can help organizations and business in many ways. Let us take a closer look.

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Healthcare

Smart machines can analyze vast chunks of data from multiple sources and identify the patterns within. When combined with IoT, ML can transform the face of healthcare. For instance, smart healthcare wearables incorporated with ML algorithms are now enabling doctors to monitor patients within the bounds of their homes. Remote monitoring has, in fact, become a boon for treating elderly patients for whom regular clinic visits can be very inconvenient. By regularly feeding personal data into the system, these smart wearables allow doctors to predict anomalies and take better decisions concerning the health of their patients.

Retail

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Yes, the online retailers you so love for curating customized recommendations for you, all rely on ML. Machine Learning algorithms learn your preference patterns and display personalized suggestions based on your previous search activity. Furthermore, ML algorithms can be very resourceful in large organizations that often fall short of human staff. Smart machines that have been designed to decipher the meaning of specific interactions (content of emails, delivery notes, etc.) can automate generic replies and help ease the burden on the company staff. This will significantly enhance the customer service experience.

Finance

In the field of finance, ML holds tremendous potential. ML algorithms can be designed to monitor potential risks in business, volatility in trade metrics, and even help investors in managing their assets better. This is primarily because ML algorithms can detect potential threats and risks in the system in real-time, and help prevent such occurrences. Also, smart machines can help you to track your spending patterns and offer customized financial advice to you.

The most noticeable contribution of ML and AI has to be voice-interaction software. Apple’s Siri, Amazon Echo’s Alexa, Microsoft’s Cortana, and Google’s Assistant are redefining the entire user experience over devices. With these virtual voice assistants, you can literally control so many activities around you, whether you want to play music, or dim the lights of your room, or know the cricket scores, it’s all possible today, thanks to AI and Machine Learning. With advanced technological innovations, in the future, it may be possible for these virtual voice assistants to be able to understand the various nuances as well as the semantics of human languages.

With so many uses and applications of Machine Learning, it is also becoming one of the most sought-after fields. Today, most of the organization with the power of data are looking to use Machine learning and related techniques to provide their customers with a better experience.

So, if you’re someone who feels the adrenaline rush just by the thought of working on Machine Learning, we recommend you check out our course on the same. From supervised learning, unsupervised learning, to even Deep Learning – our course will help you gather the required knowledge to set your feet firmly in the world of Machine Learning.

Machine Learning: A Beginner’s Guide

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As we see the world pacing towards an era where people are thriving to inculcate automaticity in everything possible, your choice of the way for blending with the advancing technology seems to be apt enough.

We won’t bore you with the well-known and overly discussed applications of this tech, like Tesla’s self-driving cars, featured recommendations on Amazon, or how machine learning is profoundly contributing in analytics, predictions, and calculations all over the world.

Rather, we’ll provide you with what you’re here for, making you dive right into the process of how machine learning actually works.

Question: How does ML work?

Answer: Algorithms!

Question: What programming language should I use to learn ML?

Answer: We have listed the languages as per the area of application and current analysis.

  • Python (used by 57% of the users):
  • Areas of application:
  • Sentiment Analysis(44%)
  • Natural Language Processing/ Chatbots(42%)
  • Web Mining(37%)
  • C/C++ (used by 43% of the users):
  • Areas of application:
  • AI in games(24%)
  • Robot Locomotion(27%)
  • Network Security and Cyber Attack Detection(26%)
  • Java (used by 41% of the users):
  • Areas of application:
  • Customer Support Management(26%)
  • Network Security and Cyber Attack Detection(23%)
  • Fraud Detection(22%)
  • R (used by 31% of the users):
  • Areas of application:
  • Sentiment Analysis(13%)
  • Bioengineering/ Bioinformatics(9%)
  • JavaScript (used by 28% of the users):
  • Areas of application:
  • Customer Support Management(10%)
  • Search Engines(9%)

As you can see, currently, Python is prioritized and highly recommended for use in ML. Python provides some ML libraries like, Tensorflow, Scikit Learn, Seaborn, Matplotlib, which could be used according to your Machine Learning projects.

Question: What are the types of Machine Learning?

Answer: There are primarily three types of Machine Learning:

Supervised Learning: Here, we make the machines learn by providing them with a training data set or labeled data, which includes the input data and the answers to it, called the response values. In supervised learning, by giving the machines these examples, we train them to make predictions for calculating the response to the new input values. So, we can say that supervised learning has model training values or the already labeled data used for predictions in future problems. Example: Using the previous house sales, we can predict the house sales in future.

Unsupervised Learning: Unlike supervised learning, in unsupervised learning, we do not have historical labels for prediction. In this case, we train the system to draw inferences from the input data without the labeled responses, look for patterns in the data and find a structure in it. For example, from the given information about heights and weights for the breeds of dogs, the computer can identify which breed does the dog belongs to.

Reinforcement Learning: We can say that this type of machine learning is inspired by behaviorist psychology, i.e., the computer learns decision making on its own using trial and error methods. Here, we train our computer by telling it, on its every move, that whether it made a right decision or not. This way, it gets to learn by its own behavior and implements this learning in the future decisions.

For problem-solving in ML, you’ll have to analyze the type of problem and try to figure out that which area of Machine Learning would be considered best for solving it. Once you know it, you can use the concerned algorithms for the solutions.

If you have decided to go further in this field, these are some of the algorithms you will get your hands on while solving the problems using ML:

Classification Algorithms

Anomaly Detection Algorithm

Regression Algorithm

Clustering Algorithm

Reinforcement Algorithm

For solving any problem using machine learning, you’ll have to carry out certain steps, that are, acquiring the data, cleaning the data, performing train test split, training the model using the training set, and at last, evaluating the model using the test set.

What we’ve talked about, is enough to give you a fair bit of insights into the world of Machine Learning. However, it goes without saying that AI and ML are the widest spreading fields of our time. It’s only fair to say that if you’re interested in this domain, you should look for courses that’ll help you get deeper insights.

Oh, did we say ML courses? We, at Coding Ninjas, have both offline as well as an online course for Machine Learning where we talk in depth about everything you need to know if you’re setting out to master Machine Learning. We recommend you give us a visit!

Java vs. C/CPP for competitive programming

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If you’re here, chances are, you’ve decided to enter the world of competitive programming. And now, like every other fresher, you’re confused about the language to pick, right?

Java vs. C/CPP has been an ongoing debate since the advent of the competitive program. None of these languages trump the others, and it’s all about your preferences and needs. However, if you’re an absolute beginner, these key points will help you make a more informed decision:

  1. C/CPP:
  • C++ does not force object-oriented programming:  Unlike Java, the C++ language doesn’t force object-oriented programming, it merely supports. It. CPP provides useful extensions that can facilitate object-oriented programming thus allowing you to enjoy the best of both worlds.
  • Parameterized types: The “template” keyword in C++ allows the coder to write generic implementations of algorithms which can come in quite handy in the long run. In C, one could write a generic list implementation with an element like:

struct element_t
   {
      struct element_t *next, *prev;
      void *element;
   };

C++ allows you to write something like:

template <typename T>
struct element_t
{
   element_t<T> *next, *prev;
   T element;
};

  • A vast standard library:  C++, being a successor of the mighty C, allows the full use of the standard C libraries as well as the advanced libraries of C++. The most useful library is the Standard Template Library (STL). The STL contains some valuable templates like searching and sorting routines and implementation of most-used algorithms. It also includes useful data structures like maps, sets, lists, trees, graphs, etc. All of the STL routines and data structures are tailored to specific programmer needs – all the programmer has to do is fill in the types.

For example, to implement Binary Search, Java requires us to write a custom function. Whereas, in C++ Binary Search STL  routine is defined as

binary_search(startaddress, endaddress, valuetofind)

The above routine can be used without spending a lot of time on the logic behind something as trivial as binary search, thereby saving the coder’s time.

  1. Java:
  • STL vs. containers: C++ provides well designed STLs, whereas Java has Containers. The benefit of containers over STLs is that there are a few situations where STL doesn’t have a direct solution. For example, in case of priority_queue in STL, it doesn’t support decrease-key operation which is required for implementations of essential algorithms like Prim’s and Dijkstra’s.
  • Exception Handling in Java is incomparable: Java is known and appreciated for being exceptional in exception handling. It trumps C/C++ in this aspect. For example, it’s a lot easier to trace an ArrayIndexOutOfBound segmentation fault in Java.
  • Time Limit Exceeds: This is where Java comes second to C++. If you’re using Java, you might come across a TLE error due to Java being slightly slower.
  • Big integer and Regular Expressions: One of the biggest advantages of Java over C++ is the availability of libraries like Biginteger, Regular Expressions, and geometry library. These libraries make day-to-day competitive programming challenges easier to tackle.

C++ vs Java

  • Java requires more lines of code: Writing codes in Java uses a lot of syntaxes. This makes Java a great tool by providing the developers with granular control over their code. But, competitive programming demands speed, so, it’s recommended to pick Java only if you have some prior knowledge of coding in Java.    
  • STL vs. Containers: As we discussed above, STLs are tailor-made for competitive programmers, but some programmers still prefer containers.
  • C++ is more Popular: Be it the origin year or the comfort of use, but C++ outstands Java regarding the number of users that use the language.
  • C++ saves time: Java is no doubt slower than C regarding compilation and execution of the code. Couple that with the verbosity of Java codes and you’ll realize the amount of time you can save if you opt for CPP. During coding contests, you need to compile and run programs many times before you reach the desired output. Java takes a lot of time in this aspect, while C++ is a lot slower. Therefore, in limited time contests, C++ can help save time. However, many coding contests today provide different time limits for Java and C++ with that for Java being on a slightly higher end than C++. So, even if you choose Java as your sword, you won’t lose out on too much. Just be thorough in whichever language you choose.

Wrapping it up, C++ is till date the most preferred language followed by Java for competitive programming. However, ardent Java coders still use Java and beat other coders fair and square. C++ being more popular doesn’t make it the one for you. Eventually, it all boils down to your comfort and your needs. If you’ve been coding in C/C++, you shouldn’t switch to Java just because of its exception handling capabilities. Similarly, if you have a Java background and are competent at it, C++ shouldn’t be your choice only because of its benefits. Being confident in what language you chose is the key along with rigorous practice. We at Coding Ninjas make sure you don’t lack in either – come, join us, and see yourself excel!

Online vs. classroom: Which To Choose?

classroom-vs-online-which-to-pick-when (1)

 

An increasing number of people from all walks of life are waking up the importance of understanding coding and its underlying principles. From teachers, entrepreneurs, managers, inventors, to even students (not necessarily of Computer Science background), everyone is trying to get around the concepts of programming.

In today’s technology-oriented world, the knowledge of programming is an integral part of learning. Technological innovations surround us and make our lives much more convenient and reliable. If you understand the basics of coding and programming, you know how these innovations work. Not only that, but you’ll also be in a position to implement your ideas and who knows, maybe you’ll be the one creating the next big thing?

Like most advanced disciplines today, you can learn to code either by enrolling in a coding boot camp (offline) or an online coding course. Both of them have their distinct advantages and limitations. Let us get a deeper insight into them.

Classroom Coding Courses:

  1. Better guidance

It is a known fact that a classroom or boot camp environment is a highly interactive one – since you are not only surrounded by counselors and mentors, but also by your classmates. If ever you are unable to grasp a concept or are confused about something, you always have others to guide you through your weak points. Face-to-face discussions are possible in such an environment which can be quite nurturing for your coding skills.

  1. Focused curriculum

Classroom coding classes or coding boot camps usually have a stipulated period (12-15 weeks) during which they focus on teaching the basics of coding, and cover all the relevant topics that every fresher need, helping comprehensive knowledge about coding and programming. The syllabus is curated well-planned, making learning much more natural.

  1. Collaborative learning

When you learn to code in a class with fellow students, you learn to interact and collaborate with them as a team aiming to accomplish a common aim. Coding often requires a team effort and stimulates real-life challenges that you’ll face in a work environment. It’s a great experience to have!

  1. Networking

Coders are nothing short of a community. In a classroom coding environment, you get to meet a lot of people from varied backgrounds – and consequently build good connections with them. Making right contacts and expanding your network can open the door to new possibilities. Who knows, some of these people might even be a potential future colleague!

Online Coding Courses:

  1. Flexibility

One of the most significant advantages of online coding courses is flexibility. You don’t need to commute for long hours to reach your class – your class starts right where you are! This makes it easier to learn to code as you can conveniently fit it into your schedule. You get to learn and interact with your mentor at your own pace and convenience. A survey conducted by The Learning House reported that almost 44% of students who took online courses showed remarkable improvements concerning their employment, for instance, obtaining a full-time job just within a year after graduation.

  1. Affordable courses

When you enroll in an online course, you only need to pay an online application fee, the tuition fee, and maybe spend a little more on reference book supplies. It is much more affordable than classroom courses where you have to incur transportation costs, high tuition rates, and a few other additional costs.

  1. Range of options

Online coding courses usually have a vast number of course topics under their umbrella. As you can study at your convenience, you get to choose from an array of exciting subjects – as time and location are not a limiting factor here.

  1. Self-motivation

Online learning courses demand a lot of motivation and dedication on your part. You need to chalk out deadlines for various courses and topics, and you need to fit them into your busy schedule. Gradually, you not only develop time management skills but also become much more motivated and responsible.

We, at Coding Ninjas aim to provide you the best of both worlds through our flagship online courses. From C++, Java, Machine Learning, to even interview preparation, we try to bridge the gap between online and offline learning through our unique pedagogy. Our ultimate aim is to replicate the classroom experience in our online classes. For the same reason, we have created batch walls where students can easily discuss doubts, share notes, and form a network. The teaching assistants (TAs) are available online for 6-8 hours daily to clear any doubts you have, and to help you better, we maintain a strict 10:1 ratio of students to TAs.. Everything from the instructors, course material, assignments, etc., is the same as our offline classes. You just get to learn at your own pace and time, and also earn a certificate along the way. Can’t get better!

Our online classes also provide in-house code sharing functionalities like code pair where students can seamlessly share their coding screen with teaching assistants without using a third-party application. The students can avail the benefits of text and video chat to collaborate in real-time with their TAs and classmates. If you are someone who learns better through interaction, discussions, and brainstorming sessions, then our online courses are for you! Do drop by our course page to know more. To make sure you aren’t in any sorts of double minds, we also provide a free-trial of our online classes, so that you can get the feel of what it is all about!

What are you waiting for? We have early bird discounts, too. Come on in, quick!