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Top 10 Advance Java Interview questions?

Top 10 Advance Java Interview questions?   What are the differences between abstract classes and interfaces in Java? What is the difference between ArrayList and LinkedList in Java? What is the purpose of the finalize() method in Java? What is polymorphism in Java and how is it achieved? What are the different types of inner classes in Java? What is the difference between static and non-static methods in Java? What are the different types of exceptions in Java and how do they differ? What is the difference between checked and unchecked exceptions in Java? How does Java handle multithreading and synchronization? What are the different types of JDBC drivers in Java and how do they differ?
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What is Python ? | comingfly

What is Python ?

Developed by the Python Foundation in the early 1990s, Python is a high-level programming language that has many different uses, including data science and back-end web development. As a powerful data analysis tool, it is widely used in big data technology, and a strong community of machine learning developers have helped elevate its status in the burgeoning field of artificial intelligence.

Due to this vibrant community, there are already many pre-built libraries for machine learning in Python. And Python is platform agnostic, meaning that it is adaptable to virtually any operating system. It is also open source, which makes it very accessible to the general public.

Python is a dynamically typed language, which can create problems in machine learning environments. For one, errors can become difficult to track as the program grows larger and more complex. This can create costly drawbacks and also slow down performance.

Also developed in the early 1990s, R is part of the GNU project. It is widely used in data analysis, and is typically applied to common machine learning tasks like regression, classification and decision tree formation. It is a very popular programming language among statisticians.

R is also open source and is widely renowned for being relatively easy to install, configure and use. It is platform agnostic and integrates well with other programming languages. Along with data analysis, R has particularly strong data visualization capability.

Despite being relatively easy to integrate with other tools, R has some unique quirks that can make it somewhat confusing to learn, like its unconventional data structures and indexing(which starts at 1 instead of 0). It also is less popular than Python and thus does not have as much documentation available for machine learning applications. (For more on these two languages, see The Debate Between R and Python.)
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