Category: Python

1. You have been asked to create a Pizza Ordering program that prompts the user

1. You have been asked to create a Pizza Ordering program that prompts the user to enter a number associated with a menu of options for their pizza order. The program should allow the user to select only one of the menu options (Small cheese pizza, Medium cheese pizza, Large cheese pizza). When the user specifies their menu option, they should be prompted to enter their topping choices (pepperoni, sausage, or olives) as follows: 1 to specify that they want the topping and 0 to specify that they do not want the topping. Each topping option costs $1.00 extra.
The goal is to calculate the order total based on the quantity specified for the menu option they chose and toppings. A confirmation of the order displays a ticket that shows what was ordered, the quantity, the menu item chosen, and the total price.
Example order ticket
Thank you for your order!
Quantity: 2 Item: Small cheese pizza, no toppings – $12.00
Total: $24.00
Submit your flowchart as a PNG file and your pseudocode as a TXT or DOC file.
2. Follow up Question:
Translate the algorithm described in the flowchart and pseudocode created for the Pizza Ordering Program algorithm into a Python program. Create a comment header at the top of the file using a block comment and use in-line comments to describe important sections (input, processing, and output) based on intended functionality. Test your code by compiling it to verify that it is functioning as expected and correct any syntax and/or semantic errors present (based on the programming problem).
Create a test plan using the Sample Test Plan (pdf) provided as a guide.
Submit your program as a Python (.py) file and submit your Test Plan as a PDF.ou may create your own Test Plan or use the format shown in the Sample Test Plan. Please be sure you include this with your assignment submission.
You will need to upload both files in the space provided below.

research two different aspects of programming languages, comparing and making
ju

research two different aspects of programming languages, comparing and making
judgements about them. 

conduct your own data analysis to create a shareable file that documents your fi

conduct your own data analysis to create a shareable file that documents your findings. You should start by taking a look at your dataset and brainstorming what questions you could answer using it. Then you should use pandas and NumPy to answer the questions you are most interested in, and create a report sharing the answers. You will not be required to use inferential statistics or machine learning to complete this project, but you should make it clear in your communications that your findings are tentative. This project is open-ended in that we are not looking for one right answer.
Overview and NotesThis data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue.Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters.
There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is.
The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
Example QuestionsWhich genres are most popular from year to year? What kinds of properties are associated with movies that have high revenues?

First q :
Write an algorithm to determine if a given string contains a balanced

First q :
Write an algorithm to determine if a given string contains a balanced sequence of parentheses.
Input
The input consists of a string containing “(” or “)” only.
Output
Print an Integer representing the count of balanced pairs if the string is balanced. Else print -1
Second q2:
Write an algorithm to find the number of occurrences of needle in a given positive number haystack.
Input
The first line of the input consists of an integer needle, representing a digit.
The second line consists of an integer haystack, representing the positive number.
Output
Print an integer representing the number of occurrences of needle in haystack,
Constraints
0 ≤ needle ≤ 9
0 ≤ haystack ≤ 99999999
Example
Input:
2
123228
Output:
3
Dont use chatgpt at all I can use it!!!

The initial project consisted of developing a machine learning model in Python f

The initial project consisted of developing a machine learning model in Python for a specific application or problem domain. The project requires to demonstrate the understanding of data preprocessing, model selection, evaluation metrics, and effective communication of results. This step of creating the machine learning model in Python is already finished and I will provide it to you below. For my part, the help I need is to complete a presentation where I give my feedback about how this project is progressing. Below I will leave you some of the most important requirements that this presentation needs:
Submit a progress demo recording that includes:
Data preprocessing steps and any challenges encountered.
Details of the machine learning models implemented and the rationale behind their selection.
Evaluation metrics used to assess the models’ performance.
Preliminary results and any insights gained from the analysis.
Plan for finalizing the project, including potential refinements and improvements.

Please run all this codes and implement the codes following what the output show

Please run all this codes and implement the codes following what the output shows (optimization of dropout, kernel, filters, best model). Send me the IPYNB file and the pdf file of all the codes and output

Use the dental radiograph “teeth_sample.png” in the Files section. The objective

Use the dental radiograph “teeth_sample.png” in the Files section. The objective is to detect the gaps (intensity valleys) between upper and lower teeth (horizontally oriented gap) as well as between teeth (vertically oriented gaps) in the x-ray, as described in (Jain and Chen, 2004), the slides and as was presented in class. As a preprocessing step, you may want to enhance the image (contrast); for example, in Matlab you can see: https://www.mathworks.com/help/images/adaptive-histogram-equalization.html. However, you can use any filter, or cascade of filters, to achieve what you consider as “good” input.
Jain, A.K., and Chen, H. (2004). Matching of dental X-ray images for human identification. Pattern Recognition, 37:1519-1539.
Suggestion: You may want to first detect the gap between upper and lower teeth, and then the gaps between teeth in the upper section and lower section separately. For the gaps between teeth, you can either assume a priori the number of gaps, or calculate them. Remember: there is a single gap between upper and lower teeth as (global) minimum in average intensity profile (you assume this anyway), while there are multiple (local) minima corresponding to the gaps between teeth.
The calculated gaps should be approximated with lines, 2nd degree polynomial for upper-lower, and 1st degree (straight lines) between teeth.
Input: dental radiograph image
Output: original image with calculated lines superimposed on the image
Submit:
Matlab/Python code with any additional external functions you used. [7pts]
A screen recording of your execution. [3pts]

build the following generative models to generate faces using the given dataset

build the following generative models to generate faces using the given dataset.
Dataset can be found here FaceExpressions.zip
1. a DCGAN
Evaluate the models using Inception Score and Frechet Inception Distance using a pretrained Face Detection model
Submit 5 generated faces (one for each expression in the cGAN) using each model
In a pdf report or at the top of your ipynb files, share the 5 generated faces using each model and the IS and FID metrics for each model. Clear and specific responses are expected.
Submit your ipynb file run end-to-end sequentially, and convert it to HTML.

One is example and another one is solved code, need the evaluation plots output

One is example and another one is solved code, need the evaluation plots output in the last two cells. (output is required in last 2 cells for sure )

Hi! I need you to help me to optimize my Convolutional Neural Network model. Hig

Hi! I need you to help me to optimize my Convolutional Neural Network model. Higher accuracy and lower loss. If needed adjust data augmentation and correct possible errors. Add models if necessary and add a final 5 cross validation of the final model. Here is the task of the project: Use Keras to train a neural network for the binary classification of muffins and Chihuahuas based on images from this dataset. (Kaggle muffin vs chihuahua)
Images must be transformed from JPG to RGB (or grayscale) pixel values and scaled down. The student is asked to:
experiment with different network architectures (at least 3) and training hyperparameters,
use 5-fold cross validation to compute your risk estimates,
thoroughly discuss the obtained results, documenting the influence of the choice of the network architecture and the tuning of the hyperparameters on the final cross-validated risk estimate.
While the training loss can be chosen freely, the reported cross-validated estimates must be computed according to the zero-one loss.