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
This document provides an overview of the Python programming language. It discusses that Python is an interpreted, high-level, general-purpose programming language created by Guido van Rossum in 1991. It is commonly used for web development, software development, data science, and more. The document then covers Python syntax, basic programming concepts like variables and data types, and how to set up a Python environment and write simple Python programs.
Python is a popular, high-level programming language used for web development, software development, data science, and more. It can be used to build both simple scripting programs as well as large-scale applications. Key characteristics of Python include being dynamically typed, having automatic memory management, and using indentation to define code blocks rather than curly braces. Python supports procedural, object-oriented, and functional programming styles and has a large standard library.
Python is a popular, high-level programming language used for web development, software development, data science, and more. It can be used to build both simple scripting programs as well as large-scale applications. Key characteristics of Python include being dynamically typed, having automatic memory management, and using indentation to define code blocks rather than curly braces. Python supports procedural, object-oriented, and functional programming styles and has a large standard library.
The type of a value refers to the kind of data it represents. In Python, the main types are:
- int - integer numbers like 1, 2, 100
- float - floating point numbers like 1.5, 3.14159
- str - strings, sequences of characters like 'hello'
- bool - boolean values True or False
When you write code, Python assigns a type to each value. The type determines how it can be used and what operations are valid on it. For example, you can add two integers but not add an integer to a string. Checking and understanding types is important for writing correct Python code.
Python is a general purpose programming language that can be used for both programming and scripting. It was created in the 1990s by Guido van Rossum who named it after the Monty Python comedy troupe. People use Python for a variety of tasks due to its readability, object-oriented capabilities, extensive libraries, and ability to integrate with other languages. To run Python code, it must first be compiled into bytecode which is then interpreted by the Python virtual machine.
Guido Van Rossum created the Python programming language in 1991. Some key facts about Python's history and creator include that Python was inspired by the ABC programming language and that Van Rossum named Python after the Monty Python comedy group. Python has grown tremendously over the years and is now a simple, general purpose, high-level programming language used widely for tasks like web development, data science, and artificial intelligence.
Python is a general purpose programming language that can be used for both programming and scripting. It was created in the 1990s by Guido van Rossum to address the need for a higher level language in the Amoeba operating system project. Python is widely used today for web development, science, system administration, and more due to its readability, object orientation, powerful libraries, and portability across operating systems. To use Python, one installs an IDE like Python 2.7 and then writes and runs code either in the Python command line or IDE.
Python is a widely used programming language that offers several unique features and advantages compared to languages like Java and C++. Our Python tutorial thoroughly explains Python basics and advanced concepts, starting with installation, conditional statements, loops, built-in data structures, Object-Oriented Programming, Generators, Exception Handling, Python RegEx, and many other concepts. This tutorial is designed for beginners and working professionals.
Python is an interpreted, object-oriented programming language that can be used for many types of applications. It was created by Guido van Rossum in the 1980s and takes influence from languages like ABC, Modula-3, C, C++, Algol-68, SmallTalk, and Unix shell scripting. Python code can be written and executed with either an interactive interpreter or scripts, and Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.
This document provides an overview of the Python programming language, including its history, uses, and key features. It discusses how Python is both a programming language and a scripting language. The document also covers installing Python, examples of companies that use Python, a sample Python code, and how to execute Python code.
This document provides an introduction to Python programming. It discusses the history and origins of Python, its key features and applications. Some of the main points covered include:
- Python was created in the late 1980s by Guido van Rossum and takes influence from other languages like ABC, Modula-3, C, C++ and Unix shell scripts.
- Python is an interpreted, object-oriented scripting language that is designed to be highly readable. It has applications in systems programming, GUIs, web development, data analysis, scientific computing and more.
- The document outlines Python's technical strengths like being free, portable, powerful, easy to use and learn. It also covers basics like variables,
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 is a general purpose programming language that can be used for both programming and scripting. It was created in the late 1980s by Guido van Rossum to address the limitations of other languages at the time. Python code is first compiled to bytecode, which is then executed by the Python Virtual Machine. It is an easy to use, powerful, and portable language employed by many major companies for web development, system administration, science, and more.
Mastering the Interview: 50 Common Interview Questions DemystifiedMalcolmDupri
Embark on your journey into the world of programming with this comprehensive introduction to Python. Whether you're a beginner eager to learn your first programming language or an experienced developer seeking to expand your skill set, this Slide Share presentation is the perfect starting point. From the basics of syntax and data types to more advanced concepts like functions and modules, we'll guide you through the fundamentals of Python programming in an accessible and engaging manner. By the end of this presentation, you'll have a solid understanding of Python's capabilities and be well-equipped to tackle a variety of programming challenges.
Python is an object-oriented, high-level programming language that is easy to learn and use for a variety of purposes including web and app development, data analysis, automation, and more. It can be used on many platforms and has a simple syntax that focuses on readability. Python allows for rapid prototyping and is commonly used in fields like data science where it can handle large datasets. Key benefits include its productivity, readability, extensive standard library, and ability to be extended with additional modules.
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 tutorial for beginners - Tib academyTIB Academy
Get python training through simple tutorial from TIB Academy, through this python tutorial you can lean more topics of python. you can download python tutorial free as PPT
Python is an easy to learn programming language that is widely used for a variety of tasks. It has a simple syntax that allows developers to focus on solving problems rather than dealing with complex language features. Python code can be written quickly and read easily by others. It also has a large ecosystem of libraries and frameworks that support application development, data science, machine learning, and more. While not the fastest language, Python makes up for it with versatility and the ability to connect different systems through its "glue" programming capabilities.
SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL
From Basics to Advanced: A Comprehensive Python Programming Guidepallavichauhan2525
Python's strength lies in its versatility and simplicity. Whether you’re developing small automation scripts or large-scale machine learning applications, Python provides the right tools to simplify your tasks. Its expansive library ecosystem, active community, and diverse applications make Python the language of choice for many developers.
Introduction to Python Programming BasicsDhana malar
Python is a popular high-level programming language that can be used for a wide range of applications from simple scripts to complex machine learning programs. It has a simple syntax, extensive standard library, and support for code reuse through modules and packages. Some key strengths of Python include its huge collection of standard libraries for tasks like machine learning, web development, scientific computing, and more. It is also an interpreted language, making it easy to learn and use for both simple and complex programming tasks.
Introduction to Python
What is Python?
Python is a high-level, interpreted programming language known for its simplicity and readability. It was created by Guido van Rossum and first released in 1991. Python emphasizes code readability with its clean and straightforward syntax, making it an excellent choice for beginners and experienced developers alike.
Features of Python:
Simple and Easy to Learn: Python's syntax is designed to be intuitive and readable, making it easy for beginners to grasp.
Interpreted: Python code is executed line by line by the Python interpreter, which means you can run Python code without the need for compilation.
High-Level: Python abstracts low-level details, allowing developers to focus on solving problems rather than dealing with system-level intricacies.
Dynamic Typing: Python uses dynamic typing, meaning you don't need to declare variable types explicitly. Variables can dynamically change types during execution.
Multi-paradigm: Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming.
Extensive Standard Library: Python comes with a vast standard library that provides support for various tasks like file I/O, networking, and more, making it highly versatile.
Portability: Python is available on various platforms, including Windows, macOS, and Linux, making it highly portable.
Community and Ecosystem: Python has a large and active community, contributing to a rich ecosystem of libraries and frameworks for various domains, such as web development, data science, machine learning, and more.
Use Cases of Python:
Web Development: With frameworks like Django and Flask, Python is widely used for building web applications.
Data Science: Python's rich ecosystem of libraries such as NumPy, Pandas, and Matplotlib makes it a popular choice for data analysis and visualization.
Machine Learning and AI: Libraries like TensorFlow, PyTorch, and scikit-learn enable developers to build machine learning models and AI applications efficiently.
Scripting: Python's simplicity and versatility make it ideal for writing scripts for automation, system administration, and more.
Game Development: Python is used in game development, both for writing game logic and scripting within game engines like Unity.
Installing Python:
To get started with Python, you need to install it on your system. You can download Python from the official website python.org and follow the installation instructions for your operating system.
Hello, World! Example:
Let's start with the traditional "Hello, World!" program in Python:
python
Copy code
print("Hello, World!")
This simple program prints "Hello, World!" to the console. It's a common starting point for learning any programming language.
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.
Guido Van Rossum created the Python programming language in 1991. Some key facts about Python's history and creator include that Python was inspired by the ABC programming language and that Van Rossum named Python after the Monty Python comedy group. Python has grown tremendously over the years and is now a simple, general purpose, high-level programming language used widely for tasks like web development, data science, and artificial intelligence.
Python is a general purpose programming language that can be used for both programming and scripting. It was created in the 1990s by Guido van Rossum to address the need for a higher level language in the Amoeba operating system project. Python is widely used today for web development, science, system administration, and more due to its readability, object orientation, powerful libraries, and portability across operating systems. To use Python, one installs an IDE like Python 2.7 and then writes and runs code either in the Python command line or IDE.
Python is a widely used programming language that offers several unique features and advantages compared to languages like Java and C++. Our Python tutorial thoroughly explains Python basics and advanced concepts, starting with installation, conditional statements, loops, built-in data structures, Object-Oriented Programming, Generators, Exception Handling, Python RegEx, and many other concepts. This tutorial is designed for beginners and working professionals.
Python is an interpreted, object-oriented programming language that can be used for many types of applications. It was created by Guido van Rossum in the 1980s and takes influence from languages like ABC, Modula-3, C, C++, Algol-68, SmallTalk, and Unix shell scripting. Python code can be written and executed with either an interactive interpreter or scripts, and Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.
This document provides an overview of the Python programming language, including its history, uses, and key features. It discusses how Python is both a programming language and a scripting language. The document also covers installing Python, examples of companies that use Python, a sample Python code, and how to execute Python code.
This document provides an introduction to Python programming. It discusses the history and origins of Python, its key features and applications. Some of the main points covered include:
- Python was created in the late 1980s by Guido van Rossum and takes influence from other languages like ABC, Modula-3, C, C++ and Unix shell scripts.
- Python is an interpreted, object-oriented scripting language that is designed to be highly readable. It has applications in systems programming, GUIs, web development, data analysis, scientific computing and more.
- The document outlines Python's technical strengths like being free, portable, powerful, easy to use and learn. It also covers basics like variables,
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 is a general purpose programming language that can be used for both programming and scripting. It was created in the late 1980s by Guido van Rossum to address the limitations of other languages at the time. Python code is first compiled to bytecode, which is then executed by the Python Virtual Machine. It is an easy to use, powerful, and portable language employed by many major companies for web development, system administration, science, and more.
Mastering the Interview: 50 Common Interview Questions DemystifiedMalcolmDupri
Embark on your journey into the world of programming with this comprehensive introduction to Python. Whether you're a beginner eager to learn your first programming language or an experienced developer seeking to expand your skill set, this Slide Share presentation is the perfect starting point. From the basics of syntax and data types to more advanced concepts like functions and modules, we'll guide you through the fundamentals of Python programming in an accessible and engaging manner. By the end of this presentation, you'll have a solid understanding of Python's capabilities and be well-equipped to tackle a variety of programming challenges.
Python is an object-oriented, high-level programming language that is easy to learn and use for a variety of purposes including web and app development, data analysis, automation, and more. It can be used on many platforms and has a simple syntax that focuses on readability. Python allows for rapid prototyping and is commonly used in fields like data science where it can handle large datasets. Key benefits include its productivity, readability, extensive standard library, and ability to be extended with additional modules.
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 tutorial for beginners - Tib academyTIB Academy
Get python training through simple tutorial from TIB Academy, through this python tutorial you can lean more topics of python. you can download python tutorial free as PPT
Python is an easy to learn programming language that is widely used for a variety of tasks. It has a simple syntax that allows developers to focus on solving problems rather than dealing with complex language features. Python code can be written quickly and read easily by others. It also has a large ecosystem of libraries and frameworks that support application development, data science, machine learning, and more. While not the fastest language, Python makes up for it with versatility and the ability to connect different systems through its "glue" programming capabilities.
SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL SAMCSCMLA SCACLSALS CS L LSLSL
From Basics to Advanced: A Comprehensive Python Programming Guidepallavichauhan2525
Python's strength lies in its versatility and simplicity. Whether you’re developing small automation scripts or large-scale machine learning applications, Python provides the right tools to simplify your tasks. Its expansive library ecosystem, active community, and diverse applications make Python the language of choice for many developers.
Introduction to Python Programming BasicsDhana malar
Python is a popular high-level programming language that can be used for a wide range of applications from simple scripts to complex machine learning programs. It has a simple syntax, extensive standard library, and support for code reuse through modules and packages. Some key strengths of Python include its huge collection of standard libraries for tasks like machine learning, web development, scientific computing, and more. It is also an interpreted language, making it easy to learn and use for both simple and complex programming tasks.
Introduction to Python
What is Python?
Python is a high-level, interpreted programming language known for its simplicity and readability. It was created by Guido van Rossum and first released in 1991. Python emphasizes code readability with its clean and straightforward syntax, making it an excellent choice for beginners and experienced developers alike.
Features of Python:
Simple and Easy to Learn: Python's syntax is designed to be intuitive and readable, making it easy for beginners to grasp.
Interpreted: Python code is executed line by line by the Python interpreter, which means you can run Python code without the need for compilation.
High-Level: Python abstracts low-level details, allowing developers to focus on solving problems rather than dealing with system-level intricacies.
Dynamic Typing: Python uses dynamic typing, meaning you don't need to declare variable types explicitly. Variables can dynamically change types during execution.
Multi-paradigm: Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming.
Extensive Standard Library: Python comes with a vast standard library that provides support for various tasks like file I/O, networking, and more, making it highly versatile.
Portability: Python is available on various platforms, including Windows, macOS, and Linux, making it highly portable.
Community and Ecosystem: Python has a large and active community, contributing to a rich ecosystem of libraries and frameworks for various domains, such as web development, data science, machine learning, and more.
Use Cases of Python:
Web Development: With frameworks like Django and Flask, Python is widely used for building web applications.
Data Science: Python's rich ecosystem of libraries such as NumPy, Pandas, and Matplotlib makes it a popular choice for data analysis and visualization.
Machine Learning and AI: Libraries like TensorFlow, PyTorch, and scikit-learn enable developers to build machine learning models and AI applications efficiently.
Scripting: Python's simplicity and versatility make it ideal for writing scripts for automation, system administration, and more.
Game Development: Python is used in game development, both for writing game logic and scripting within game engines like Unity.
Installing Python:
To get started with Python, you need to install it on your system. You can download Python from the official website python.org and follow the installation instructions for your operating system.
Hello, World! Example:
Let's start with the traditional "Hello, World!" program in Python:
python
Copy code
print("Hello, World!")
This simple program prints "Hello, World!" to the console. It's a common starting point for learning any programming language.
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.
Active Server Pages (ASP) is a technology developed by Microsoft that allows for the creation of dynamic web pages. ASP code is written within HTML pages and is executed on the server, with the output being standard HTML sent to the browser. This allows web pages to incorporate server-side scripting for functionality like dynamically updating content and connecting to databases. The document discusses the key differences between static and dynamic web pages, and provides examples of using common ASP objects and components like Request, Response, Session, and Server to handle tasks like form submission, setting cookies and headers, and managing user sessions.
The document discusses various techniques for representing and describing image regions after segmentation. It describes choosing external or internal representation based on focusing on shape or region properties. Common representation techniques include chain codes, polygonal approximations, signatures, boundary segments, and skeletons. Descriptors are then used to represent regions in a compact, invariant form for further processing and analysis.
This document discusses biologically inspired computation and ant colony optimization algorithms. It begins by explaining that inspiration from swarm intelligence has led to successful optimization algorithms like ant colony optimization and particle swarm optimization. The document then focuses on ant colony optimization, describing how ants demonstrate emergent problem solving through behaviors like regulating nest temperature, forming bridges, sorting items, and finding the shortest route to food sources. These swarm behaviors emerge from individual ants following simple rules. The ant colony optimization algorithm is inspired by how ants communicate indirectly using pheromone trails to solve problems in an emergent, decentralized manner.
EE 520 is an image analysis and computer vision class that meets Monday, Wednesday, and Tuesday-Thursday. The class will be evaluated based on two projects worth 30% each and a midterm worth 40%. Projects will include a report, presentation, and MATLAB code. The class will cover topics like feature extraction, segmentation, registration, optical flow, shape representation, tracking, recognition, and inferring 3D structure from 2D images. Example applications include analyzing faces, objects, activities, leaf motion, and beating hearts.
The document presents an overview of automatic question paper generators (AQPG). It discusses how AQPGs work by gathering questions from banks and generating papers based on algorithms that consider factors like difficulty levels, topic weights, and syllabus coverage. The document reviews various algorithms used in AQPGs, such as randomized algorithms and artificial intelligence techniques like genetic algorithms and natural language processing. It also provides a literature survey summarizing over 20 research papers on AQPGs and the algorithms they employed. Finally, it concludes that AQPGs can help standardize the question paper generation process and reduce the workload for educators.
an insightful lecture on "Loads on Structure," where we delve into the fundamental concepts and principles of load analysis in structural engineering. This presentation covers various types of loads, including dead loads, live loads, as well as their impact on building design and safety. Whether you are a student, educator, or professional in the field, this lecture will enhance your understanding of ensuring stability. Explore real-world examples and best practices that are essential for effective engineering solutions.
A lecture by Eng. Wael Almakinachi, M.Sc.
Computer Graphics: Application of Computer Graphics.
OpenGL: Introduction to OpenGL,coordinate reference frames, specifying two-dimensional world coordinate
reference frames in OpenGL, OpenGL point functions, OpenGL line functions, point attributes, line attributes,
curve attributes, OpenGL fill area functions, OpenGL Vertex arrays, Line drawing algorithm- Bresenham'S
This research is oriented towards exploring mode-wise corridor level travel-time estimation using Machine learning techniques such as Artificial Neural Network (ANN) and Support Vector Machine (SVM). Authors have considered buses (equipped with in-vehicle GPS) as the probe vehicles and attempted to calculate the travel-time of other modes such as cars along a stretch of arterial roads. The proposed study considers various influential factors that affect travel time such as road geometry, traffic parameters, location information from the GPS receiver and other spatiotemporal parameters that affect the travel-time. The study used a segment modeling method for segregating the data based on identified bus stop locations. A k-fold cross-validation technique was used for determining the optimum model parameters to be used in the ANN and SVM models. The developed models were tested on a study corridor of 59.48 km stretch in Mumbai, India. The data for this study were collected for a period of five days (Monday-Friday) during the morning peak period (from 8.00 am to 11.00 am). Evaluation scores such as MAPE (mean absolute percentage error), MAD (mean absolute deviation) and RMSE (root mean square error) were used for testing the performance of the models. The MAPE values for ANN and SVM models are 11.65 and 10.78 respectively. The developed model is further statistically validated using the Kolmogorov-Smirnov test. The results obtained from these tests proved that the proposed model is statistically valid.
This slide deck presents a detailed overview of the 2025 survey paper titled “A Survey of Personalized Large Language Models” by Liu et al. It explores how foundation models like GPT and LLaMA can be personalized to better reflect user-specific needs, preferences, and behaviors.
The presentation is structured around a 3-level taxonomy introduced in the paper:
Input-Level Personalization (e.g., user-profile prompting, memory retrieval)
Model-Level Personalization (e.g., LoRA, PEFT, adapters)
Objective-Level Personalization (e.g., RLHF, preference alignment)
How to Buy Snapchat Account A Step-by-Step Guide.pdfjamedlimmk
Scaling Growth with Multiple Snapchat Accounts: Strategies That Work
Operating multiple Snapchat accounts isn’t just a matter of logging in and out—it’s about crafting a scalable content strategy. Businesses and influencers who master this can turn Snapchat into a lead generation engine.
Key strategies include:
Content Calendars for Each Account – Plan distinct content buckets and themes per account to avoid duplication and maintain variety.
Geo-Based Content Segmentation – Use location-specific filters and cultural trends to speak directly to a region's audience.
Audience Mapping – Tailor messaging for niche segments: Gen Z, urban youth, gamers, shoppers, etc.
Metrics-Driven Storytelling – Use Snapchat Insights to monitor what type of content performs best per account.
Each account should have a unique identity but tie back to a central brand voice. This balance is crucial for brand consistency while leveraging the platform’s creative freedoms.
How Agencies and Creators Handle Bulk Snapchat Accounts
Digital agencies and creator networks often manage dozens—sometimes hundreds—of Snapchat accounts. The infrastructure to support this requires:
Dedicated teams for each cluster of accounts
Cloud-based mobile device management (MDM) systems
Permission-based account access for role clarity
Workflow automation tools (Slack, Trello, Notion) for content coordination
This is especially useful in verticals such as music promotion, event marketing, lifestyle brands, and political outreach, where each campaign needs targeted messaging from different handles.
The Legality and Risk Profile of Bulk Account Operations
If your aim is to operate or acquire multiple Snapchat accounts, understand the risk thresholds:
Personal Use (Low Risk) – One or two accounts for personal and creative projects
Business Use (Medium Risk) – Accounts with aligned goals, managed ethically
Automated Bulk Use (High Risk) – Accounts created en masse or used via bots are flagged quickly
Snapchat uses advanced machine learning detection for unusual behavior, including:
Fast switching between accounts from the same IP
Identical Snap stories across accounts
Rapid follower accumulation
Use of unverified devices or outdated OS versions
To stay compliant, use manual operations, vary behavior, and avoid gray-market account providers.
Smart Monetization Through Multi-Account Snapchat Strategies
With a multi-account setup, you can open doors to diversified monetization:
Affiliate Marketing – Niche accounts promoting targeted offers
Sponsored Content – Brands paying for story placement across multiple profiles
Product Launch Funnels – Segment users by interest and lead them to specific landing pages
Influencer Takeovers – Hosting creators across multiple themed accounts for event buzz
This turns your Snapchat network into a ROI-driven asset instead of a time sink.
Conclusion: Build an Ecosystem, Not Just Accounts
When approached correctly, multiple Snapchat accounts bec
The TRB AJE35 RIIM Coordination and Collaboration Subcommittee has organized a series of webinars focused on building coordination, collaboration, and cooperation across multiple groups. All webinars have been recorded and copies of the recording, transcripts, and slides are below. These resources are open-access following creative commons licensing agreements. The files may be found, organized by webinar date, below. The committee co-chairs would welcome any suggestions for future webinars. The support of the AASHTO RAC Coordination and Collaboration Task Force, the Council of University Transportation Centers, and AUTRI’s Alabama Transportation Assistance Program is gratefully acknowledged.
This webinar overviews proven methods for collaborating with USDOT University Transportation Centers (UTCs), emphasizing state departments of transportation and other stakeholders. It will cover partnerships at all UTC stages, from the Notice of Funding Opportunity (NOFO) release through proposal development, research and implementation. Successful USDOT UTC research, education, workforce development, and technology transfer best practices will be highlighted. Dr. Larry Rilett, Director of the Auburn University Transportation Research Institute will moderate.
For more information, visit: https://aub.ie/trbwebinars
Dear SICPA Team,
Please find attached a document outlining my professional background and experience.
I remain at your disposal should you have any questions or require further information.
Best regards,
Fabien Keller
Jacob Murphy Australia - Excels In Optimizing Software ApplicationsJacob Murphy Australia
In the world of technology, Jacob Murphy Australia stands out as a Junior Software Engineer with a passion for innovation. Holding a Bachelor of Science in Computer Science from Columbia University, Jacob's forte lies in software engineering and object-oriented programming. As a Freelance Software Engineer, he excels in optimizing software applications to deliver exceptional user experiences and operational efficiency. Jacob thrives in collaborative environments, actively engaging in design and code reviews to ensure top-notch solutions. With a diverse skill set encompassing Java, C++, Python, and Agile methodologies, Jacob is poised to be a valuable asset to any software development team.
1. Introduction to
Python
Programming
Python is a powerful and versatile programming language that has
become increasingly popular in recent years. It's known for its clear
syntax and beginner-friendliness, making it ideal for both learning
and building complex applications. Python has a huge community
of developers, making it easy to find help and resources.
by Vijaya Lakshmi A
3. What is Python?
Python is a high-level, interpreted programming language. Its design focuses
on code readability and simplicity. This makes it easier to write and maintain
code, even for complex projects. Python can be used for various tasks,
including web development, data science, machine learning, scripting, and
more.
Easy to Learn
Python's syntax is intuitive and
straightforward, making it a
great choice for beginners.
Versatile
It can be used for a wide range
of applications, from simple
scripts to complex software.
Large Community
There's a vast community of
Python developers, providing
ample resources and support.
Cross-Platform
Python runs on various
operating systems, including
Windows, macOS, Linux, and
Unix.
4. Why Learn Python?
Learning Python opens doors to exciting career opportunities and personal projects. With its widespread use, Python skills are highly sought
after in various industries. Furthermore, Python's versatility allows you to explore different areas of programming and pursue your interests.
1 High Demand
Python skills are in high demand in the tech industry, leading
to lucrative career paths.
2 Versatile Applications
Python can be used for web development, data analysis,
automation, and more.
3 Growing Community
The Python community is vast and supportive, providing
abundant resources and help.
4 Open Source
Python is an open-source language, meaning it's free to use
and modify.
5. • Invented at Netherlands,early 90s by Guido
van Rossum
• Named after Monty Python
• Open sourced, Scalable, object oriented and
functionalProgramminglanguage
• Used by Google as one of its official
programming language
• Increasingly popular
Python - Introduction
6. Python’s Benevolent Dictator For Life
“Python is an experiment in
how much freedom program-
mers need. Too much freedom
and nobody can read another's
code; too little and expressive-
ness is endangered.”
- Guido van Rossum
8. • Call python program via the python interpreter
% python fact.py
• Make a python file directly executable by
–Adding the appropriate path to your python
interpreter as the first line of your file
#!/usr/bin/python
–Making the file executable
% chmod a+x fact.py
–Invoking file from Unix command line
% fact.py
Running Programs on UNIX
9. • In interactive mode, you type Python programs, and
the interpreter displays the result.
$python 3
>>> 2 + 3
>>> 5
• python3 command enters into python prompt.
• >>> is called the Python prompt in linux.
• The interpreter evaluates the expression and
replies. New prompt indicates it is ready for more
input.
• Working directly in the interpreter is convenient for testing
short bits of code because we get immediate feedback.
Interactive Mode
10. The set of Python instructions are written in a file called as
program with extension .py also called as script.
The program file is referred as source code.
The compiler is used to convert the source code to byte code.
The interpreter is used to interpret the byte code and produce the
result.
$ g ed i t f i r s t . py
# F i r s t Program
Script Mode
11. • Indentation matters to code meaning
–Block structure indicated by indentation
• First assignment to a variable creates it
–Variable types don’t need to be declared.
–Python figures out the variable types on its own.
• Assignment is = and comparison is ==
• For numbers + - * / % are as expected
–Special use of + for string concatenation and % for string formatting
(as in C’s printf)
• Logical operators are words (and, or, not) not
symbols
• The basic printing command is print
Enough to Understand the Code
12. Naming Rules
• Names are case sensitive and cannot
start with a number. They can contain
letters, numbers, and underscores.
bob Bob _bob _2_bob_
bob_2 BoB
• There are some reserved words:
and, assert, break, class,
continue, def, del, elif,
else, except, exec, finally,
for, from, global, if,
import, in, is, lambda, not,
or, pass, print, raise,
return, try, while
13. Operators and Expressions
Operators are symbols that perform specific operations on values. Expressions are combinations of operators and values that result in a new value. Understanding these is essential for
writing calculations, comparisons, and logical operations.
Operator Description
+ Addition
- Subtraction
* Multiplication
/ Division
== Equality
!= Inequality
< Less than
> Greater than
14. In Python, the input() function is used to take input from the user. This function reads a line from input (usually
from the keyboard), converts it into a string, and returns it.
Basic Usage of input()
Here is the basic syntax for the input() function:
By default, input() returns a string. If you need to handle other data types (like integers or floats), you'll need to
convert the input using typecasting:
16. In Python, the print() function is the most commonly used statement for
displaying output. It allows you to print text, variables, and formatted data to the
console.
19. Python Libraries and Frameworks
Python's vast collection of libraries and frameworks extends its capabilities. Libraries provide pre-written code for
various tasks, saving you time and effort. Frameworks provide a structure for building applications, simplifying the
development process.
Web Development
Frameworks like Django and Flask
simplify web application
development.
Data Science
Libraries like NumPy, Pandas, and
Matplotlib are essential for data
analysis and visualization.
Machine Learning
Libraries like scikit-learn, TensorFlow,
and PyTorch empower you to build
machine learning models.