This document contains frequently asked Python interview questions organized into different sections like Python fundamentals, OOPs concepts, Pandas, Numpy etc. It begins with introductory questions about Python's history, benefits, dynamic and interpreted nature. Then it covers core concepts like data types, modules, scopes, lists vs tuples. The document also includes questions on OOPs concepts, Pandas for data analysis, Numpy for numerical computing and commonly used Python libraries. It ends with examples of Python programs to solve different problems.
Python is an interpreted, general-purpose programming language with a simple syntax that emphasizes readability. It supports object-oriented programming, threads, exception handling, and automatic memory management. Some key benefits of Python include its readability, modularity through third-party packages, and large community for rapid application development. Python is dynamically typed, meaning variables are not explicitly declared as a particular type and can hold values of different types during runtime.
This presentation provides an introduction to the Python programming language. It covers Python's basics like data types, variables, conditional statements, loops, functions, modules, file handling, object-oriented programming concepts, and popular Python libraries for data science like Pandas, Django, and Numpy. The goal is to give attendees a solid understanding of Python and how it is used widely in fields like data science, machine learning, and artificial intelligence.
Python – The Fastest Growing Programming LanguageIRJET Journal
1) Python is a widely used general-purpose programming language known for its simplicity and readability. It has seen rapid growth in recent years driven by its popularity for data science and machine learning tasks.
2) Key reasons for Python's growth include its use in academia and industries like software, manufacturing, and electronics. It is also popular due to its extensive libraries for tasks like data analysis and its job opportunities for data scientists.
3) Python supports multiple programming paradigms, has a large standard library, and can be used for web development, desktop GUIs, system scripting, and more. Its simplicity, readability, and extensive community make it a good choice for both learning and real-world programming
This document provides an introduction to using Python for biologists. It discusses what Python is, gives examples of using it to calculate areas in flowcharts, and demonstrates how to print and manipulate text in Python. The document is divided into chapters that cover topics like why Python is suitable for biologists, printing messages, using quotes, comments, and error handling. Examples are provided throughout to illustrate concepts.
Python is a general-purpose, high-level programming language that is widely used for web and application development, data science, and machine learning. It was created by Guido van Rossum in 1991 and takes inspiration from languages like C, Java, Lisp, and Modula-3. Python code is human-readable and has an easy to learn syntax that uses indentation rather than brackets to indicate blocks of code. It supports multiple programming paradigms including object-oriented, imperative, and functional programming.
Python’s versatility and readability make it an ideal language for developers across diverse domains. By following best practices and enrolling in a Python training course in cities across India, you can harness Python’s full potential, advance your career, and contribute to the ever-growing Python community. Whether you’re a beginner or an experienced coder, the journey of mastering Python is both rewarding and limitless.
Tweepy is an open source Python package that gives you a very convenient way to access the Twitter API with Python. Tweepy includes a set of classes and methods that represent Twitter's models and API endpoints, and it transparently handles various implementation details, such as: Data encoding and decoding.
Python is an interpreted, object-oriented programming language that has gained widespread popularity. According to a 2018 Stack Overflow survey, 38.8% of respondents predominantly use Python for their work, surpassing languages like C# and PHP. Python has a simple syntax, is readable, and has a large community and libraries for tasks like data science, web development, and machine learning. Popular Python libraries include TensorFlow for machine learning, NumPy for numerical computing, Pandas for data analysis, Keras for artificial neural networks, and Matplotlib for plotting.
Python is an interpreted, general-purpose programming language with a simple syntax that emphasizes readability. It supports object-oriented programming, threads, exception handling, and automatic memory management. Some key benefits of Python include its readability, modularity through third-party packages, and large community for rapid application development. Python is dynamically typed, meaning variables are not explicitly declared as a particular type and can hold values of different types during runtime.
This presentation provides an introduction to the Python programming language. It covers Python's basics like data types, variables, conditional statements, loops, functions, modules, file handling, object-oriented programming concepts, and popular Python libraries for data science like Pandas, Django, and Numpy. The goal is to give attendees a solid understanding of Python and how it is used widely in fields like data science, machine learning, and artificial intelligence.
Python – The Fastest Growing Programming LanguageIRJET Journal
1) Python is a widely used general-purpose programming language known for its simplicity and readability. It has seen rapid growth in recent years driven by its popularity for data science and machine learning tasks.
2) Key reasons for Python's growth include its use in academia and industries like software, manufacturing, and electronics. It is also popular due to its extensive libraries for tasks like data analysis and its job opportunities for data scientists.
3) Python supports multiple programming paradigms, has a large standard library, and can be used for web development, desktop GUIs, system scripting, and more. Its simplicity, readability, and extensive community make it a good choice for both learning and real-world programming
This document provides an introduction to using Python for biologists. It discusses what Python is, gives examples of using it to calculate areas in flowcharts, and demonstrates how to print and manipulate text in Python. The document is divided into chapters that cover topics like why Python is suitable for biologists, printing messages, using quotes, comments, and error handling. Examples are provided throughout to illustrate concepts.
Python is a general-purpose, high-level programming language that is widely used for web and application development, data science, and machine learning. It was created by Guido van Rossum in 1991 and takes inspiration from languages like C, Java, Lisp, and Modula-3. Python code is human-readable and has an easy to learn syntax that uses indentation rather than brackets to indicate blocks of code. It supports multiple programming paradigms including object-oriented, imperative, and functional programming.
Python’s versatility and readability make it an ideal language for developers across diverse domains. By following best practices and enrolling in a Python training course in cities across India, you can harness Python’s full potential, advance your career, and contribute to the ever-growing Python community. Whether you’re a beginner or an experienced coder, the journey of mastering Python is both rewarding and limitless.
Tweepy is an open source Python package that gives you a very convenient way to access the Twitter API with Python. Tweepy includes a set of classes and methods that represent Twitter's models and API endpoints, and it transparently handles various implementation details, such as: Data encoding and decoding.
Python is an interpreted, object-oriented programming language that has gained widespread popularity. According to a 2018 Stack Overflow survey, 38.8% of respondents predominantly use Python for their work, surpassing languages like C# and PHP. Python has a simple syntax, is readable, and has a large community and libraries for tasks like data science, web development, and machine learning. Popular Python libraries include TensorFlow for machine learning, NumPy for numerical computing, Pandas for data analysis, Keras for artificial neural networks, and Matplotlib for plotting.
Python is a high-level programming language for computers that gives instructions on how to do something. It has efficient high-level data structures and a simple but effective object-oriented programming style. Python is a high-level computer programming language that is meant to represent the needs of a problem and looks like natural language or mathematical notation. It is a free language with open-source code. This means that the source code of Python scripts is free to read, change, and share. Python is a language that is used to interpret other languages. Tutorials Freak is an online resource that offers tutorials on cutting-edge software and hardware. It also has a Python tutorial that's been put together by the field's experts in such an easy-to-understand way. It will really make it easier for you to learn.
"Level up your coding game with our dynamic Python course. From beginner to pro, master the language that's taking the tech world by storm. Join us now and unlock your full potential!"
Introduction to python -easiest way to understand python for beginners
What is Python…?
Differences between programming and scripting language
Programming Paradigms
History of Python
Scope of Python
Why do people use Python?
Installing Python
This document outlines a 3-week roadmap to become a Python expert from beginner. Week 1 focuses on fundamentals like syntax, variables, control flow, and functions. Week 2 covers intermediate concepts such as data structures, file handling, and exception handling. Week 3 explores advanced topics including object-oriented programming, database connectivity, and specializing in web development or data analysis. The document also recommends a Python training course in Gurgaon to help accelerate the learning process.
The major Python updated 2023 intel document 12.docxintel-writers.com
Python is an ocean of libraries that serve various purposes and as a Python developer, you must have sound knowledge of the best ones. To help you in this, here is an article that brings to you the Top 10 Python Libraries for machine learning which are:
• Tensor Flow
• Sickest-Learn
• Numpy
• Keras
• PyTorch
• LightGBM
• Eli5
• SciPy
• Theano
• Pandas
•
Python is one of the most popular and widely used programming languages and has replaced many programming languages in the industry.
There are a lot of reasons why Python is popular among developers and one of them is that it has an amazingly large collection of libraries that users can work with. To learn more about Python, you can join our Python certification course today.
Here are a few important reasons as to why Python is popular:
• Python has a huge collection of libraries.
• Python is a beginner’s level programming language because of it simplicity and easiness.
• From developing to deploying and maintaining Python wants their developers to be more productive.
• Portability is another reason for huge popularity of Python.
• Python programming syntax is simple to learn and is of high level when we compare it to C, Java, and C++.
Hence, only a few lines of code make new applications.
The simplicity of Python has attracted many developers to create new libraries for machine learning. Because of the huge collection of libraries Python is becoming hugely popular among machine learning experts.
This document summarizes a MOOC course on Python taken through the Udemy platform. The 35.5 hour course was created by Jose Salvatierra and teaches Python programming fundamentals through video lectures, presentations, quizzes and coding exercises over 4 weeks. Key topics covered include Python syntax, object oriented programming, graphical user interfaces, databases, and how Python can be applied to build complex AI products and address issues like bias, attacks, and ethics. Upon completion, students will have skills in core Python programming, OOP, GUI development, and database applications.
Python is a powerful and object-oriented programming language that has grown rapidly in popularity due to its simplicity and flexibility. It supports multiple programming paradigms and has a large standard library. Python source code is first compiled to bytecode, which is then executed by the Python Virtual Machine. While Java may be faster for single algorithms, Python is easier for beginners to learn and its dynamic typing and automatic memory management make programs quicker to write. It has gained widespread use for web development, data science, and scripting.
Python, the versatile and powerful programming language, has gained immense popularity in recent years. Its simplicity, readability, and vast array of libraries make it an ideal language for both beginners and experienced programmers. Whether you’re looking to kickstart a career in software development or enhance your existing programming skills, mastering Python is a valuable asset.
WHY
WHERE
HOW
WHEN
WHO
FOR WHAT
Defining Data Science
• What Does a Data Science Professional Do?
• Data Science in Business
• Use Cases for Data Science
The document outlines an introduction to Python guest lecture covering setting up a Python development environment, Python basics syntax including variables, data types, functions and flow control, sample Python programs, and continuing your Python learning journey with additional concepts and a quiz. The lecture agenda includes explaining Python basics, demonstrating sample programs, taking questions, and clearing doubts. The speaker has 17 years of IT industry experience and is sharing their Python expertise in this lecture.
Python A Comprehensive Guide for Beginners.pdfKajal Digital
Welcome to the exciting world of Python programming! If you're a beginner eager to dive into the world of coding, you've chosen an excellent starting point. Python is often heralded as one of the most beginner-friendly programming languages, and it's widely used in fields such as web development, data analysis, scientific research, and artificial intelligence. Why Python? It's known for its clean and readable syntax, making it almost like writing in plain English. Whether you dream of creating web applications, automating repetitive tasks, or delving into data science, Python is your go-to tool.
This document provides an overview of the Python programming language. It states that Python is a high-level, general-purpose programming language created by Guido van Rossum in 1991. Python emphasizes code readability and allows programmers to develop applications rapidly. It has a simple syntax compared to languages like C and C++. Python also supports cross-platform development and has a comprehensive standard library. The document discusses popular Python libraries, IDEs, and notebooks for data science and machine learning tasks. It provides examples of basic data types in Python and highlights advantages like requiring less code and programming time.
This document provides a comprehensive guide to mastering Python programming. It begins with an introduction to Python and its wide applications. The guide then covers Python fundamentals like installation, variables, data types, conditional statements, loops, functions. It discusses Python data structures like lists, tuples, dictionaries and popular libraries. It also explains object-oriented programming concepts in Python like classes, inheritance and exception handling. Finally, the conclusion emphasizes that Python is a powerful language for developers of all skill levels due to its versatile features and libraries.
Python is a widely-used, high-level programming language known for its simplicity, readability, and extensive library support. It is favored by developers for its ease of use and ability to handle diverse tasks, making it suitable for various applications ranging from web development to data analysis and artificial intelligence.
Python, the versatile and powerful programming language, has firmly established itself as one of the most popular and widely used programming languages in the world. It’s known for its simplicity, readability, and flexibility, making it an excellent choice for both beginners and experienced developers. What sets Python apart from other languages is its incredible range of applications, from web development to data analysis, scientific computing, machine learning, and more. In this article, we’ll explore how to harness the full potential of Python through projects, practice, and proficiency.
This document outlines the objectives and content of the course GE3151 Problem Solving and Python Programming. The course is intended to teach students the basics of algorithmic problem solving using Python. It covers topics like computational thinking, Python data types, control flow, functions, strings, lists, tuples, dictionaries, files and modules. The course contains 5 units that will teach students how to define problems, develop algorithms, implement solutions in Python using conditionals, loops, functions and data structures, perform input/output with files and use modules and packages.
If you're referring to acquisitions made by companies prior to the implementation of the Goods and Services Tax (GST), here are some acquisitions that occurred before GST was introduced:
Facebook (Meta Platforms, Inc.):
Instagram (Acquired in 2012)
WhatsApp (Acquired in 2014)
Oculus VR (Acquired in 2014)
Alphabet Inc. (Google):
YouTube (Acquired in 2006)
DoubleClick (Acquired in 2008)
Nest Labs (Acquired in 2014)
Amazon:
Zappos (Acquired in 2009)
Twitch (Acquired in 2014)
Microsoft Corporation:
LinkedIn (Acquired in 2016)
Skype (Acquired in 2011)
Apple Inc.:
Beats Electronics (Acquired in 2014)
Shazam (Acquisition announced in 2017, completed in 2018)
Oracle Corporation:
Sun Microsystems (Acquired in 2010)
Siebel Systems (Acquired in 2006)
IBM (International Business Machines Corporation):
Cognos (Acquired in 2007)
SPSS (Acquired in 2009)
Salesforce:
Tableau Software (Acquired in 2019)
MuleSoft (Acquired in 2018)
Cisco Systems:
WebEx (Acquired in 2007)
Meraki (Acquired in 2012)
Intel Corporation:
McAfee (Acquired in 2011)
Altera Corporation (Acquired in 2015)
These are just a few examples of acquisitions made by companies prior to the implementation of GST. These acquisitions have played significant roles in shaping the strategies and offerings of these tech giants.
If you're referring to acquisitions made by companies prior to the implementation of the Goods and Services Tax (GST), here are some acquisitions that occurred before GST was introduced:
Facebook (Meta Platforms, Inc.):
Instagram (Acquired in 2012)
WhatsApp (Acquired in 2014)
Oculus VR (Acquired in 2014)
Alphabet Inc. (Google):
YouTube (Acquired in 2006)
DoubleClick (Acquired in 2008)
Nest Labs (Acquired in 2014)
Amazon:
Zappos (Acquired in 2009)
Twitch (Acquired in 2014)
Microsoft Corporation:
LinkedIn (Acquired in 2016)
Skype (Acquired in 2011)
Apple Inc.:
Beats Electronics (Acquired in 2014)
Shazam (Acquisition announced in 2017, completed in 2018)
Oracle Corporation:
Sun Microsystems (Acquired in 2010)
Siebel Systems (Acquired in 2006)
IBM (International Business Machines Corporation):
Cognos (Acquired in 2007)
SPSS (Acquired in 2009)
Salesforce:
Tableau Software (Acquired in 2019)
MuleSoft (Acquired in 2018)
Cisco Systems:
WebEx (Acquired in 2007)
Meraki (Acquired in 2012)
Intel Corporation:
McAfee (Acquired in 2011)
Altera Corporation (Acquired in 2015)
These are just a few examples of acquisitions made by companies prior to the implementation of GST. These acquisitions have played significant roles in shaping the strategies and offerings of these tech giants.
If you're referring to acquisitions made by companies prior to the implementation of the Goods and Services Tax (GST), here are some acquisitions that occurred before GST was introduced:
Facebook (Meta Platforms, Inc.):
Instagram (Acquired in 2012)
WhatsApp (Acquired in 2014)
Oculus VR (Acquired in 2014)
Alphabet Inc. (Google):
YouTube (Acquired in 2006)
DoubleClick (Acquired in 2008)
Nest Labs (Acquired in 2014
Python is a high-level programming language for computers that gives instructions on how to do something. It has efficient high-level data structures and a simple but effective object-oriented programming style. Python is a high-level computer programming language that is meant to represent the needs of a problem and looks like natural language or mathematical notation. It is a free language with open-source code. This means that the source code of Python scripts is free to read, change, and share. Python is a language that is used to interpret other languages. Tutorials Freak is an online resource that offers tutorials on cutting-edge software and hardware. It also has a Python tutorial that's been put together by the field's experts in such an easy-to-understand way. It will really make it easier for you to learn.
"Level up your coding game with our dynamic Python course. From beginner to pro, master the language that's taking the tech world by storm. Join us now and unlock your full potential!"
Introduction to python -easiest way to understand python for beginners
What is Python…?
Differences between programming and scripting language
Programming Paradigms
History of Python
Scope of Python
Why do people use Python?
Installing Python
This document outlines a 3-week roadmap to become a Python expert from beginner. Week 1 focuses on fundamentals like syntax, variables, control flow, and functions. Week 2 covers intermediate concepts such as data structures, file handling, and exception handling. Week 3 explores advanced topics including object-oriented programming, database connectivity, and specializing in web development or data analysis. The document also recommends a Python training course in Gurgaon to help accelerate the learning process.
The major Python updated 2023 intel document 12.docxintel-writers.com
Python is an ocean of libraries that serve various purposes and as a Python developer, you must have sound knowledge of the best ones. To help you in this, here is an article that brings to you the Top 10 Python Libraries for machine learning which are:
• Tensor Flow
• Sickest-Learn
• Numpy
• Keras
• PyTorch
• LightGBM
• Eli5
• SciPy
• Theano
• Pandas
•
Python is one of the most popular and widely used programming languages and has replaced many programming languages in the industry.
There are a lot of reasons why Python is popular among developers and one of them is that it has an amazingly large collection of libraries that users can work with. To learn more about Python, you can join our Python certification course today.
Here are a few important reasons as to why Python is popular:
• Python has a huge collection of libraries.
• Python is a beginner’s level programming language because of it simplicity and easiness.
• From developing to deploying and maintaining Python wants their developers to be more productive.
• Portability is another reason for huge popularity of Python.
• Python programming syntax is simple to learn and is of high level when we compare it to C, Java, and C++.
Hence, only a few lines of code make new applications.
The simplicity of Python has attracted many developers to create new libraries for machine learning. Because of the huge collection of libraries Python is becoming hugely popular among machine learning experts.
This document summarizes a MOOC course on Python taken through the Udemy platform. The 35.5 hour course was created by Jose Salvatierra and teaches Python programming fundamentals through video lectures, presentations, quizzes and coding exercises over 4 weeks. Key topics covered include Python syntax, object oriented programming, graphical user interfaces, databases, and how Python can be applied to build complex AI products and address issues like bias, attacks, and ethics. Upon completion, students will have skills in core Python programming, OOP, GUI development, and database applications.
Python is a powerful and object-oriented programming language that has grown rapidly in popularity due to its simplicity and flexibility. It supports multiple programming paradigms and has a large standard library. Python source code is first compiled to bytecode, which is then executed by the Python Virtual Machine. While Java may be faster for single algorithms, Python is easier for beginners to learn and its dynamic typing and automatic memory management make programs quicker to write. It has gained widespread use for web development, data science, and scripting.
Python, the versatile and powerful programming language, has gained immense popularity in recent years. Its simplicity, readability, and vast array of libraries make it an ideal language for both beginners and experienced programmers. Whether you’re looking to kickstart a career in software development or enhance your existing programming skills, mastering Python is a valuable asset.
WHY
WHERE
HOW
WHEN
WHO
FOR WHAT
Defining Data Science
• What Does a Data Science Professional Do?
• Data Science in Business
• Use Cases for Data Science
The document outlines an introduction to Python guest lecture covering setting up a Python development environment, Python basics syntax including variables, data types, functions and flow control, sample Python programs, and continuing your Python learning journey with additional concepts and a quiz. The lecture agenda includes explaining Python basics, demonstrating sample programs, taking questions, and clearing doubts. The speaker has 17 years of IT industry experience and is sharing their Python expertise in this lecture.
Python A Comprehensive Guide for Beginners.pdfKajal Digital
Welcome to the exciting world of Python programming! If you're a beginner eager to dive into the world of coding, you've chosen an excellent starting point. Python is often heralded as one of the most beginner-friendly programming languages, and it's widely used in fields such as web development, data analysis, scientific research, and artificial intelligence. Why Python? It's known for its clean and readable syntax, making it almost like writing in plain English. Whether you dream of creating web applications, automating repetitive tasks, or delving into data science, Python is your go-to tool.
This document provides an overview of the Python programming language. It states that Python is a high-level, general-purpose programming language created by Guido van Rossum in 1991. Python emphasizes code readability and allows programmers to develop applications rapidly. It has a simple syntax compared to languages like C and C++. Python also supports cross-platform development and has a comprehensive standard library. The document discusses popular Python libraries, IDEs, and notebooks for data science and machine learning tasks. It provides examples of basic data types in Python and highlights advantages like requiring less code and programming time.
This document provides a comprehensive guide to mastering Python programming. It begins with an introduction to Python and its wide applications. The guide then covers Python fundamentals like installation, variables, data types, conditional statements, loops, functions. It discusses Python data structures like lists, tuples, dictionaries and popular libraries. It also explains object-oriented programming concepts in Python like classes, inheritance and exception handling. Finally, the conclusion emphasizes that Python is a powerful language for developers of all skill levels due to its versatile features and libraries.
Python is a widely-used, high-level programming language known for its simplicity, readability, and extensive library support. It is favored by developers for its ease of use and ability to handle diverse tasks, making it suitable for various applications ranging from web development to data analysis and artificial intelligence.
Python, the versatile and powerful programming language, has firmly established itself as one of the most popular and widely used programming languages in the world. It’s known for its simplicity, readability, and flexibility, making it an excellent choice for both beginners and experienced developers. What sets Python apart from other languages is its incredible range of applications, from web development to data analysis, scientific computing, machine learning, and more. In this article, we’ll explore how to harness the full potential of Python through projects, practice, and proficiency.
This document outlines the objectives and content of the course GE3151 Problem Solving and Python Programming. The course is intended to teach students the basics of algorithmic problem solving using Python. It covers topics like computational thinking, Python data types, control flow, functions, strings, lists, tuples, dictionaries, files and modules. The course contains 5 units that will teach students how to define problems, develop algorithms, implement solutions in Python using conditionals, loops, functions and data structures, perform input/output with files and use modules and packages.
If you're referring to acquisitions made by companies prior to the implementation of the Goods and Services Tax (GST), here are some acquisitions that occurred before GST was introduced:
Facebook (Meta Platforms, Inc.):
Instagram (Acquired in 2012)
WhatsApp (Acquired in 2014)
Oculus VR (Acquired in 2014)
Alphabet Inc. (Google):
YouTube (Acquired in 2006)
DoubleClick (Acquired in 2008)
Nest Labs (Acquired in 2014)
Amazon:
Zappos (Acquired in 2009)
Twitch (Acquired in 2014)
Microsoft Corporation:
LinkedIn (Acquired in 2016)
Skype (Acquired in 2011)
Apple Inc.:
Beats Electronics (Acquired in 2014)
Shazam (Acquisition announced in 2017, completed in 2018)
Oracle Corporation:
Sun Microsystems (Acquired in 2010)
Siebel Systems (Acquired in 2006)
IBM (International Business Machines Corporation):
Cognos (Acquired in 2007)
SPSS (Acquired in 2009)
Salesforce:
Tableau Software (Acquired in 2019)
MuleSoft (Acquired in 2018)
Cisco Systems:
WebEx (Acquired in 2007)
Meraki (Acquired in 2012)
Intel Corporation:
McAfee (Acquired in 2011)
Altera Corporation (Acquired in 2015)
These are just a few examples of acquisitions made by companies prior to the implementation of GST. These acquisitions have played significant roles in shaping the strategies and offerings of these tech giants.
If you're referring to acquisitions made by companies prior to the implementation of the Goods and Services Tax (GST), here are some acquisitions that occurred before GST was introduced:
Facebook (Meta Platforms, Inc.):
Instagram (Acquired in 2012)
WhatsApp (Acquired in 2014)
Oculus VR (Acquired in 2014)
Alphabet Inc. (Google):
YouTube (Acquired in 2006)
DoubleClick (Acquired in 2008)
Nest Labs (Acquired in 2014)
Amazon:
Zappos (Acquired in 2009)
Twitch (Acquired in 2014)
Microsoft Corporation:
LinkedIn (Acquired in 2016)
Skype (Acquired in 2011)
Apple Inc.:
Beats Electronics (Acquired in 2014)
Shazam (Acquisition announced in 2017, completed in 2018)
Oracle Corporation:
Sun Microsystems (Acquired in 2010)
Siebel Systems (Acquired in 2006)
IBM (International Business Machines Corporation):
Cognos (Acquired in 2007)
SPSS (Acquired in 2009)
Salesforce:
Tableau Software (Acquired in 2019)
MuleSoft (Acquired in 2018)
Cisco Systems:
WebEx (Acquired in 2007)
Meraki (Acquired in 2012)
Intel Corporation:
McAfee (Acquired in 2011)
Altera Corporation (Acquired in 2015)
These are just a few examples of acquisitions made by companies prior to the implementation of GST. These acquisitions have played significant roles in shaping the strategies and offerings of these tech giants.
If you're referring to acquisitions made by companies prior to the implementation of the Goods and Services Tax (GST), here are some acquisitions that occurred before GST was introduced:
Facebook (Meta Platforms, Inc.):
Instagram (Acquired in 2012)
WhatsApp (Acquired in 2014)
Oculus VR (Acquired in 2014)
Alphabet Inc. (Google):
YouTube (Acquired in 2006)
DoubleClick (Acquired in 2008)
Nest Labs (Acquired in 2014
Networking-Interview-Questions-Answers.pdfSamir Paul
The document provides a mnemonic device to help remember the 7 layers of the OSI model. The acronym "Aj Phir Se Test Nahi Dena Padega" is used, with each letter corresponding to a layer: A for Application layer, P for Presentation layer, S for Session layer, T for Transport layer, N for Network layer, D for Data link layer, and P for Physical layer.
This document contains an overview of object-oriented programming (OOP) concepts and common OOP interview questions. It begins with basic questions about OOP terms and features like classes, objects, encapsulation, inheritance and polymorphism. It then covers more advanced topics such as the differences between compile-time and runtime polymorphism, abstract classes, interfaces and access specifiers. The document provides examples in C++ and Java to illustrate various OOP concepts.
MySQL is an open-source relational database management system. It runs on servers and the web to store and retrieve data in the form of tables containing rows and columns. The document provides an overview of MySQL and answers 32 common interview questions about MySQL, ranging from basic topics like what MySQL is and how to create databases and tables, to more advanced topics like scaling, sharding, and transaction storage engines in MySQL.
This document is a collection of system design interview questions and solutions authored by Antonio Gulli. It covers topics such as basic knowledge about time, storage, networking and costs that are important for system design interviews. It also provides the fundamental steps for system design interviews which include scoping the problem, verifying requirements, drawing a high-level abstract design, and discussing tradeoffs. The document contains over 30 questions related to distributed systems, caching, load balancing, databases, and designing large-scale systems. It also includes solutions and designs for several projects such as photo hosting, distributed caching, URL shortening, and search engines.
This document provides an overview of application servers, including their history, role in web applications, and common features. Application servers act as a middle tier between database servers and end users, providing business logic, security, and other services. They first emerged to help share capabilities between applications and make applications easier to write and maintain. Common application server types include web information servers, component servers, and active application servers. Selection of an application server depends on factors like performance, cost, development needs, and support requirements.
DBMS-Handwritten-Notes-All-Concepts.pdf
Notes for Database Management System - DBMS
In these “DBMS Handwritten Notes PDF”, we will study the foundations of database management systems focusing on the significance of a database, relational data model, schema creation and normalization, transaction processing, indexing, and the relevant data structures (files and B+-trees).
We have provided multiple complete DBMS Notes PDF for any university student of BCA, MCA, B.Sc, B.Tech CSE, M.Tech branch to enhance more knowledge about the subject and to score better marks in the exam. Students can easily make use of all these DBMS Notes PDF by downloading them.
Topics in our DBMS Handwritten Notes PDF
The topics we will cover in these DBMS Handwritten Notes PDF will be taken from the following list:
Introductory Concepts of DBMS: Introduction and application of DBMS, Data Independence, Database System Architecture – levels, Mapping, Database users and DBA, Entity-Relationship model, constraints, keys, Design issues, E-R Diagram, Extended E-R features- Generalization, Specialization, Aggregation, Translating E-R model into Relational model.
Relational Model: The relational Model, The catalog, Types, Keys, Relational Algebra, Fundamental operations, Additional Operations, SQL fundamentals, DDL, DML, DCL PL/SQL Concepts, Cursors, Stored Procedures, Stored Functions, Database Integrity – Triggers.
Functional Dependencies: Non-loss Decomposition, First, Second, Third Normal Forms, Dependency Preservation, Boyce/Codd Normal Form, Multi-valued Dependencies and Fourth Normal Form, Join Dependencies, and Fifth Normal Form.
Transaction Management: ACID properties, serializability of Transaction, Testing for Serializability and concurrency control, Lock based concurrency control (2PL, Deadlocks), Time stamping methods, Database recovery management.
Implementation Techniques: Overview of Physical Storage Media, File Organization, Indexing and Hashing, B+ tree Index Files, Query Processing Overview, Catalog Information for Cost Estimation, Selection Operation, Sorting, Join Operation, Materialized views, Database Tuning.
Database Management System Note pdf download - handwrittenLectureNotes for free
Last Minute Notes – DBMS
Difficulty Level : Medium
Last Updated : 01 Jun, 2022
See Last Minute Notes on all subjects here.
We will discuss the important key points useful for GATE exams in summarized form. For details you may refer this.
E-R Diagram: The most common asked questions in ER diagram is minimum number of tables required for a given ER diagram. Generally, following criteria are used:
Cardinality Minimum No. of tables
1:1 cardinality with partial participation of both entities 2
1:1 cardinality with total participation of atleast 1 entity 1
1:n cardinality 2
m:n cardinality 3
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.