This document discusses using calculus in programming. It provides examples of defining functions in functional programming languages like Scheme. It discusses evaluating expressions by replacing formal parameters with actual parameters. An example program in C++ is provided that calculates the derivative of an expression using the power rule.
1 Planning the Computer Program
2 Uses of Algorithm
3 Flow Charts
4 Pseudo code Applications: To produce an ordered sequence of steps, that describe solution of a problem.
1 Anne complains that defining functions to use in her programs is a lot of ...hwbloom59
1 Anne complains that defining functions to use in her programs is a lot of
extra work. She says she can finish her programs much more quickly if
she just writes them using the basic operators and control statements.
State three reasons why her view is shortsighted.
2. Draw a structure chart for one of the solutions to the programming projects
of Chapters 4 and 5. The program should include at least two function
definitions other than the main function.
3 The factorial of a positive integer n, fact(n), is defined recursively as
follows:
fact(n)=1,when n=1
fact(n) = n*fact(n–1), otherwise
Define a recursive function fact that returns the factorial of a given
positive integer.
4. Write the code in python for a mapping that generates a list of the absolute values
of the numbers in a list named numbers.
1 Planning the Computer Program
2 Uses of Algorithm
3 Flow Charts
4 Pseudo code Applications: To produce an ordered sequence of steps, that describe solution of a problem.
1 Anne complains that defining functions to use in her programs is a lot of ...hwbloom59
1 Anne complains that defining functions to use in her programs is a lot of
extra work. She says she can finish her programs much more quickly if
she just writes them using the basic operators and control statements.
State three reasons why her view is shortsighted.
2. Draw a structure chart for one of the solutions to the programming projects
of Chapters 4 and 5. The program should include at least two function
definitions other than the main function.
3 The factorial of a positive integer n, fact(n), is defined recursively as
follows:
fact(n)=1,when n=1
fact(n) = n*fact(n–1), otherwise
Define a recursive function fact that returns the factorial of a given
positive integer.
4. Write the code in python for a mapping that generates a list of the absolute values
of the numbers in a list named numbers.
Learning to write programs using selection
Condition: Relational and Logical Expressions , Conditional Statements (if statement) , Choosing from Multiple Alternatives
Exercises in writing conditions using relational, logical operations, writing programs involving if statement, if-else, if- elseif and switch case statements in MATLAB
Arrays
Array Creation , Accessing Elements
Sub Arrays, Representation, Operations
Maximum and Minimum values in Matrix
Potential Energy-Spring Problem
SUMMARY
This power point presentation explains briefly about the possible arithmetic operations in pointers. It also explains implicit and explicit typecasting of pointers
Textbook Solutions refer https://pythonxiisolutions.blogspot.com/
Practical's Solutions refer https://prippython12.blogspot.com/
Self Invocation is useful in Functions, that is how it gets its name Recursion.
Recursive Function
Recursion Vs Iteration
How recursion works?
Binary Search-Recursive implementation
What is Relational model
Characteristics
Relational constraints
Representation of schemas
characteristics and Constraints of Relational model with proper examples.
Updates and dealing with constraint violations in Relational model
JLK Chapter 5 – Methods and ModularityDRAFT January 2015 Edition.docxvrickens
JLK Chapter 5 – Methods and ModularityDRAFT January 2015 Edition pg. 25
An Introduction to
Computer Science with Java, Python and C++
Community College of Philadelphia edition
Copyright 2017 by C.W. Herbert, all rights reserved.
Last edited October 8, 28, 2019 by C. W. Herbert
This document is a draft of a chapter from An Introduction to Computer Science with Java, Python and C++, written by Charles Herbert. It is available free of charge for students in Computer Science courses at Community College of Philadelphia during the Fall 2019 semester. It may not be reproduced or distributed for any other purposes without proper prior permission.
Please report any typos, other errors, or suggestions for improving the text to [email protected]
Chapter 5 – Python Functions and Modular Programming
Contents
Lesson 5.1User Created Functions in Python2
Python Function Parameters2
Value returning functions3
Example – Methods and Parameter Passing5
9
Lesson 5.2Top-Down Design and Modular Development10
Chapter Exercises13
User Created Functions in Python
So far we have only created software with one continuous Python script. We have used functions from other python modules, such as the square root method from the math class math.sqrt(n). Now we will begin to create our own functions of our own.
A Python function is a block of code that can be used to perform a specific task within a larger computer program. It can be called as needed from other Python software. Most programming languages have similar features, such as methods in Java or subroutines in system software.
The code for user-defined functions in Python is contained in a function definition. A Python function definition is a software unit with a header and a block of Python statements. The header starts with the keyword def followed by the name of the function, then a set parenthesis with any parameters for the function. A colon is used after the parentheses to indicate a block of code follows, just as with the if and while statements. The block of code to be included within the function is indented.
Here is an example of a Python function:
# firstFunction.py
# first demonstration of the use of a function for CSCI 111
# last edited 10/08/2o19 by C. Herbert
function
definition
def myFunction():
print ( "This line being printed by the function MyFunction.\n")
# end myFunction()
### main program ###
function used by the main part of the script
print("Beginning\n")
myFunction()
print("End\n")
# end main program
Functions can used for code that will be repeated within a program, or for modular development, in which long programs are broken into parts and the parts are developed independently. The parts can be developed as Python functions, then integrated to work together by being called from other software.
Python Function Parameters
Data can be passed to a Python function as a parameter of the function. Function parameters are variables listed in parentheses foll ...
Learning to write programs using selection
Condition: Relational and Logical Expressions , Conditional Statements (if statement) , Choosing from Multiple Alternatives
Exercises in writing conditions using relational, logical operations, writing programs involving if statement, if-else, if- elseif and switch case statements in MATLAB
Arrays
Array Creation , Accessing Elements
Sub Arrays, Representation, Operations
Maximum and Minimum values in Matrix
Potential Energy-Spring Problem
SUMMARY
This power point presentation explains briefly about the possible arithmetic operations in pointers. It also explains implicit and explicit typecasting of pointers
Textbook Solutions refer https://pythonxiisolutions.blogspot.com/
Practical's Solutions refer https://prippython12.blogspot.com/
Self Invocation is useful in Functions, that is how it gets its name Recursion.
Recursive Function
Recursion Vs Iteration
How recursion works?
Binary Search-Recursive implementation
What is Relational model
Characteristics
Relational constraints
Representation of schemas
characteristics and Constraints of Relational model with proper examples.
Updates and dealing with constraint violations in Relational model
JLK Chapter 5 – Methods and ModularityDRAFT January 2015 Edition.docxvrickens
JLK Chapter 5 – Methods and ModularityDRAFT January 2015 Edition pg. 25
An Introduction to
Computer Science with Java, Python and C++
Community College of Philadelphia edition
Copyright 2017 by C.W. Herbert, all rights reserved.
Last edited October 8, 28, 2019 by C. W. Herbert
This document is a draft of a chapter from An Introduction to Computer Science with Java, Python and C++, written by Charles Herbert. It is available free of charge for students in Computer Science courses at Community College of Philadelphia during the Fall 2019 semester. It may not be reproduced or distributed for any other purposes without proper prior permission.
Please report any typos, other errors, or suggestions for improving the text to [email protected]
Chapter 5 – Python Functions and Modular Programming
Contents
Lesson 5.1User Created Functions in Python2
Python Function Parameters2
Value returning functions3
Example – Methods and Parameter Passing5
9
Lesson 5.2Top-Down Design and Modular Development10
Chapter Exercises13
User Created Functions in Python
So far we have only created software with one continuous Python script. We have used functions from other python modules, such as the square root method from the math class math.sqrt(n). Now we will begin to create our own functions of our own.
A Python function is a block of code that can be used to perform a specific task within a larger computer program. It can be called as needed from other Python software. Most programming languages have similar features, such as methods in Java or subroutines in system software.
The code for user-defined functions in Python is contained in a function definition. A Python function definition is a software unit with a header and a block of Python statements. The header starts with the keyword def followed by the name of the function, then a set parenthesis with any parameters for the function. A colon is used after the parentheses to indicate a block of code follows, just as with the if and while statements. The block of code to be included within the function is indented.
Here is an example of a Python function:
# firstFunction.py
# first demonstration of the use of a function for CSCI 111
# last edited 10/08/2o19 by C. Herbert
function
definition
def myFunction():
print ( "This line being printed by the function MyFunction.\n")
# end myFunction()
### main program ###
function used by the main part of the script
print("Beginning\n")
myFunction()
print("End\n")
# end main program
Functions can used for code that will be repeated within a program, or for modular development, in which long programs are broken into parts and the parts are developed independently. The parts can be developed as Python functions, then integrated to work together by being called from other software.
Python Function Parameters
Data can be passed to a Python function as a parameter of the function. Function parameters are variables listed in parentheses foll ...
Functions - C Programming
What is a Function? A function is combined of a block of code that can be called or used anywhere in the program by calling the name. ...
Function arguments. Functions are able to accept input parameters in the form of variables. ...
Function return values
Note: This slide was created by me. I am Md. Touhidul Islam Shawan. Here in these slide I have written about some basic points of function of c program and how the function works.
Now we discuss job analysis:
We discuss its outcome, uses of job analysis information,
job analysis process (steps), method of job analysis information, writing a job description, writing a job specification,
If any confusion then tells in the comment section.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Show drafts
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
1. Introduction of calculus
in programming
Is it possible to write calculus function for c.
It would be very useful, I am sure it is possible because
there are math programs out there today
2. Use of calculus in programming
A program in a functional language is a set of function definitions and an
expression usually
formed using the defined functions. The Interpreter of the language evaluates this
expression by
means of a discrete number of computation steps, in such a way its meaning turns
out to be
represented in an explicit way. In general in programming we have not to produce
anything; in
functional programming, in particular, what we modify is only the representation
of the
information.
A function can be defined in several ways.
3. Example:
f: R -> R , g: R -> R
f '' - 6g' = 6 sin x
6g'' + a2 f ' = 6 cos x
f(0) = 0, f '(0) = 0, g(0) = 1, g'(0) = 1
This set of equations precisely identify two precise f and g.
4. To evaluate an expression in Scheme
the application of a function to some arguments and then to evaluate the body of the
function
in which the formal parameter is replaced by the actual parameter. In this way, in a
sense, we
make the meaning of such sub-expression more explicit.
5. Example: let us evaluate Inctwo 3
Inctwo 3 Inctwo is a user defined function, and it is applied to an argument, so we take
the
body of the function, replace the formal parameter n by the actual parameter 3,
obtaining
3+2, and then we evaluate 3+2 obtaining 5
6. evaluation strategy
a policy enabling to decide on which sub-expression we shall perform the next
evaluation step.
Some evaluation strategies could led me in a never ending path (this fact is
unavoidable)
7. Uses of calculus in
‘c++’ Language
#include<iostream.h>
Using name space std;
Int a,x,n,derivative;
Int main()
{
Cout<<”hellow.i am a computer program.I can calculate
the derivative of an expression using power rule.”;
Cout<<”n please type the values of a and n for use exp”;
Cout<<”n y=ax^n”;
Cin get();
Cout<<”a=?n”;
Cin>>a;
Cout<<”x=?,n=?n”
Cin>>x,n;
Derivative=a*n*(x^(n-1));
Cout<<”dy/dx=”<<derivative;
Return 0;
}