Category: Machine Learning

based on my reports results and some other reference help me finished my paper,

based on my reports results and some other reference help me finished my paper, the paper is based on AI in Nutrition and recipies

Here is my Research Topic:
Predicting Bank Failures in USA
Here is my Research

Here is my Research Topic:
Predicting Bank Failures in USA
Here is my Research Question:
Which U.S. state is most likely to experience the greatest number of bank failures in the future, and what are the main factors that contribute to this likelihood?
Here is my Dataset
Dataset Name: FDIC Failed Bank List
FDIC Failed Bank List Dataset
Download the FDIC Failed Bank List (CSV)
Here is my chosen ML Method:
Classification machine learning method
Revise and Evaluate Data Analysis Model
In this milestone, you will perform an evaluation of your data analytic model and revise your decision model as needed. For the revision, you can add in additional machine learning models or do feature engineering. You can also create confusion matrices and check for accuracy, precision, recall, or F-Measures. You can do sensitivity analyses, create ROC curves, check error rates and variable selection/feature selection. Please do see the image below for some other options for revisions:
Deliverable
For milestone 4, please ensure you have the following REQUIRED sections ONLY:
Final Research Question: Please state your final research question and describe how it evolved, if it changed, from your Milestone 1 version.
Your final research question should reflect the actual analysis you conducted and the actual insight or prediction you made. For example, if you actually ended up doing a classification task to predict the value of a response variable based on some other predictor variables, that’s what you should state as your precise, quantitative research question.
Model Revision: You should discuss how you revised your model(s) and perhaps how you narrowed down the scope of the project to something coherent and managable. In addition, you should give the details of your final machine learning model and present your final results.
Concomitantly, you should assess the robustness of your model, especially noting what makes it strong or what breaks it or the distribution of uncertainty in it. As such, you’ll likely want to utilize some variant of sensitivity analysis, depending on your particular model, to demonstrate true understanding of what the model’s doing rather than just a rote implementation thereof.
Final Results and Initial Version of Final Conclusion: You should show the initial validation of metrics and also decide upon any additional machine learning algorithms you might want to try. In addition, please ensure you answer the following questions:
What did you learn about the data?
How did you answer the questions?
How can you justify your answers?

These are questions for an Intro to Machine Learning course. Please make sure to

These are questions for an Intro to Machine Learning course. Please make sure to follow the instructions/guidelines provided to complete the assignment! This is very important! Please make sure to provide an explanation for your answers! Please show all your work, step by step! Also, please make sure to give me the solutions as a pdf file. I have attached the assignment instructions in the hw4(2).pdf file. Additionally, I have attached all the necessary files such as the data, code, and utilities files needed to complete this assignment in the hw4_code.zip file. I have also attached the Latex solution template, which is labeled as hw4_clean.tex. Let me know if you have any questions or if there’s something that you find confusing about the instructions that you would like me to clear up with you!

Solve the following three machine-learning questions using Excel.
Create or down

Solve the following three machine-learning questions using Excel.
Create or download a dataset of at least three columns and 20 rows and then do the following:
a. Solve a classification problem using KNN algorithm.
b. Solve a regression problem using KNN algorithm.
c.Solve a clustering problem using K-means algorithm.

please write a 30 slide power point ( exclude introduction, references) about fe

please write a 30 slide power point ( exclude introduction, references) about features extraction for website phishing detection datasets the instruction is the following
1) use the paper attached to describe the experiment in the paper and the steps they used for the features extraction ” all important point in the paper need to be addressed ”
2) summary of the paper need to be included
3) use other reference as needed to describe the important, the description, the kinds of features extraction in website phishing detection datasets
4) all slides need to have speaker notes to be read exactly as in the actual life and need to be different than the slides not repeat ” slides is short speaker note is the discretion”