Sunday, 24 May 2020
Our core Java programming tutorial is designed for students and working professionals. Java is an object-oriented, class-based, concurrent, secured and general-purpose computer-programming language. It is a widely used robust technology.
What is Java
Java is a programming language and a platform. Java is a high level, robust, object-oriented and secure programming language.
Java was developed by Sun Microsystems (which is now the subsidiary of Oracle) in the year 1995. James Gosling is known as the father of Java. Before Java, its name was Oak. Since Oak was already a registered company, so James Gosling and his team changed the Oak name to Java.
Platform: Any hardware or software environment in which a program runs, is known as a platform. Since Java has a runtime environment (JRE) and API, it is called a platform.
Let's have a quick look at Java programming example. A detailed description of Hello Java example is available in next page.Test it Now
According to Sun, 3 billion devices run Java. There are many devices where Java is currently used. Some of them are as follows:
- Desktop Applications such as acrobat reader, media player, antivirus, etc.
- Web Applications such as irctc.co.in, javatpoint.com, etc.
- Enterprise Applications such as banking applications.
- Embedded System
- Smart Card
- Games, etc.
Types of Java Applications
There are mainly 4 types of applications that can be created using Java programming:
1) Standalone Application
Standalone applications are also known as desktop applications or window-based applications. These are traditional software that we need to install on every machine. Examples of standalone application are Media player, antivirus, etc. AWT and Swing are used in Java for creating standalone applications.
2) Web Application
An application that runs on the server side and creates a dynamic page is called a web application. Currently, Servlet, JSP, Struts, Spring, Hibernate, JSF, etc. technologies are used for creating web applications in Java.
3) Enterprise Application
An application that is distributed in nature, such as banking applications, etc. is called enterprise application. It has advantages of the high-level security, load balancing, and clustering. In Java, EJB is used for creating enterprise applications.
4) Mobile Application
An application which is created for mobile devices is called a mobile application. Currently, Android and Java ME are used for creating mobile applications.
Java Platforms / Editions
There are 4 platforms or editions of Java:
1) Java SE (Java Standard Edition)
It is a Java programming platform. It includes Java programming APIs such as java.lang, java.io, java.net, java.util, java.sql, java.math etc. It includes core topics like OOPs, String, Regex, Exception, Inner classes, Multithreading, I/O Stream, Networking, AWT, Swing, Reflection, Collection, etc.
2) Java EE (Java Enterprise Edition)
It is an enterprise platform which is mainly used to develop web and enterprise applications. It is built on the top of the Java SE platform. It includes topics like Servlet, JSP, Web Services, EJB, JPA, etc.
3) Java ME (Java Micro Edition)
It is a micro platform which is mainly used to develop mobile applications.
It is used to develop rich internet applications. It uses a light-weight user interface API.
To learn Java, you must have the basic knowledge of C/C++ programming language.
Our Java programming tutorial is designed to help beginners and professionals.
We assure that you will not find any problem in this Java tutorial. However, if there is any mistake, please post the problem in the contact form.
Difference between Artificial intelligence and Machine learning
Artificial intelligence and machine learning are the part of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems.
Although these are two related technologies and sometimes people use them as a synonym for each other, but still both are the two different terms in various cases.
On a broad level, we can differentiate both AI and ML as:
AI is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior, whereas, machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.
Below are some main differences between AI and machine learning along with the overview of Artificial intelligence and machine learning.
Artificial intelligence is a field of computer science which makes a computer system that can mimic human intelligence. It is comprised of two words "Artificial" and "intelligence", which means "a human-made thinking power." Hence we can define it as,
Artificial intelligence is a technology using which we can create intelligent systems that can simulate human intelligence.
The Artificial intelligence system does not require to be pre-programmed, instead of that, they use such algorithms which can work with their own intelligence. It involves machine learning algorithms such as Reinforcement learning algorithm and deep learning neural networks. AI is being used in multiple places such as Siri, Google?s AlphaGo, AI in Chess playing, etc.
Based on capabilities, AI can be classified into three types:
- Weak AI
- General AI
- Strong AI
Currently, we are working with weak AI and general AI. The future of AI is Strong AI for which it is said that it will be intelligent than humans.
Machine learning is about extracting knowledge from the data. It can be defined as,
Machine learning is a subfield of artificial intelligence, which enables machines to learn from past data or experiences without being explicitly programmed.
Machine learning enables a computer system to make predictions or take some decisions using historical data without being explicitly programmed. Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate result or give predictions based on that data.
Machine learning works on algorithm which learn by it?s own using historical data. It works only for specific domains such as if we are creating a machine learning model to detect pictures of dogs, it will only give result for dog images, but if we provide a new data like cat image then it will become unresponsive. Machine learning is being used in various places such as for online recommender system, for Google search algorithms, Email spam filter, Facebook Auto friend tagging suggestion, etc.
It can be divided into three types:
- Supervised learning
- Reinforcement learning
- Unsupervised learning
Key differences between Artificial Intelligence (AI) and Machine learning (ML):
|Artificial Intelligence||Machine learning|
|Artificial intelligence is a technology which enables a machine to simulate human behavior.||Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.|
|The goal of AI is to make a smart computer system like humans to solve complex problems.||The goal of ML is to allow machines to learn from data so that they can give accurate output.|
|In AI, we make intelligent systems to perform any task like a human.||In ML, we teach machines with data to perform a particular task and give an accurate result.|
|Machine learning and deep learning are the two main subsets of AI.||Deep learning is a main subset of machine learning.|
|AI has a very wide range of scope.||Machine learning has a limited scope.|
|AI is working to create an intelligent system which can perform various complex tasks.||Machine learning is working to create machines that can perform only those specific tasks for which they are trained.|
|AI system is concerned about maximizing the chances of success.||Machine learning is mainly concerned about accuracy and patterns.|
|The main applications of AI are Siri, customer support using catboats, Expert System, Online game playing, intelligent humanoid robot, etc.||The main applications of machine learning are Online recommender system, Google search algorithms, Facebook auto friend tagging suggestions, etc.|
|On the basis of capabilities, AI can be divided into three types, which are, Weak AI, General AI, and Strong AI.||Machine learning can also be divided into mainly three types that are Supervised learning, Unsupervised learning, and Reinforcement learning.|
|It includes learning, reasoning, and self-correction.||It includes learning and self-correction when introduced with new data.|
|AI completely deals with Structured, semi-structured, and unstructured data.||Machine learning deals with Structured and semi-structured data.|