What have you done so far?

By
Responsive Centered Red Button

Need Help with this Question or something similar to this? We got you! Just fill out the order form (follow the link below), and your paper will be assigned to an expert to help you ASAP.

Order Form

This is a 3 part project in AI. First part is the Proposal so we need to hash out a small realistic proposal for a grad student who works full-time and is not a computer programmer. Simple is key here. If you read through the entire description and whats expected think about the minimalist idea we can go with. I dont care about getting an A in this. A solid B is perfect. Please reach out with questions and communication on this and the subsequent tasks are key.
AI Project
Description
The purpose of the course project is to give you an opportunity to tie together all the concepts, topics, and technologies we’ve discussed by pursuing an artificial intelligence topic of your choice. The basic idea is that you would pick one of the neural network methods, such as Convolutional Neural Networks, and train and assess an AI model using some dataset within some application domain or use-case scenario. You would then write a report describing your results, along with a section where you would comment on this project idea from a due diligence standpoint.
Each person in the class is meant to do their own project. This is not meant to be a large project, nor are you expected to perform ground-breaking or otherwise theoretical research. However, you are expected to use an AI method based on neural networks, not just a typical ML approach like logistic regression as your main model — you can use other approaches as your baseline if you would like. One example way to think of this project is for you to design a pilot project or prototype where you apply AI to solve some problem or to create a new product or application for your company. You can build your project on other code, as long as you provide citations and clearly identify your original contributions. And there should be some sort of analysis section where you detail and analyze the performance of your code in comparison to some baseline. As you know, larger datasets can require tremendous computational and time resources, so I am only expecting you to use the resources on your own computer. That said, part of your challenge is limiting the study enough so that you are able to finish the project in time. Also, we will be using Python in the course, so please write your project in Python so that I will be able to run the code if needed. And please be mindful of any proprietary or privacy issues regarding the data, as you would need to submit everything (code + data) along with your final report.
Example Project Ideas
This project gives you the opportunity to explore AI methods or datasets or application areas that interest and excite you. Here are a few ideas, though you are welcome to propose a project not on the list (the examples give you the spirit of project intent and scope):
Create a mini pilot project to solve a problem at your workplace
Apply an AI method to a dataset we did not use in the class
Create a demo and tutorial for an AI model we did not cover in class, such as Generative Adversarial Networks
Explore openai.com  (Links to an external site.)and implement Q-learning
Explore embedded ML: see the book *TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers* by Pete Warden and Daniel Situnayake
Example Project Titles
Here are some example project titles just to give you even more ideas for how to choose your own project. You are not meant to do projects with these titles–rather, you are to choose your own project, but hopefully these examples will help spark your interest and creativity, as well as focus your thinking as we proceed through the semester’s lecture and reading materials.
“Deep Learning with Transfer Learning for Celebrity Look-alike Recognition”
“Application of the Convolutional Neural Network Architecture for Image Classification using Custom Created Images Composed of Digitally Drawn Digits”
“Comparing Machine Learning Algorithms to a Fully Connected Neural Network for Ship Recognition”
“Stock Analyzer for Predictive Choices”
“Cyber Attack Prediction”
“Learning-Based Intrusion Detection Systems”
“Real Time Image Caption Generator”
“The Deer Finding Project”
“Classifying Road Surface Abnormalities”
“Supervised Learning to Predict Talent Pools for a More Robust Targeted Recruitment Strategy by Using Human Resources Data”
“Automatically Detecting Malaria using Cell Images”
“Anomaly-Based Time-Series Forecasting for CPU Usage Predictive Alerting”
“Analyzing Real versus Fake Bird Images using Deep Convolutional General Adversarial Networks”
“Landmark Image Recognition with Convolutional Neural Networks”
“The experimental application of a pretrained Mask Regional-Convolutional Neural Networkfor developing search and rescue processes”
“The Maddening Madness of March”
“Using Machine Learning to Predict Future Price Direction of Invesco’s QQQ ETF”
“Facial Recognition for Contactless Entry & Enhanced Security”
“Anomaly Detection using Computer Vision”
“Deep Learning Models Used for Sentiment Analysis of Tweets to Increase Customer Service”
“Covid-19 Detection with X-ray images utilizing Convolutional Neural Networks”
Project Deliverables
To help give you structure within which to plan and implement your project, here are the project deadlines:
MAR 20: Project Proposal due [10%]
APR 17: Project Milestone due [20%]
MAY 8: Final project due (report pdf and zip of code/data) [70%]
Datasets
There are many datasets available online:
ImageNet (Links to an external site.)
Dataset Search (Links to an external site.) – Google’s Dataset search engine blog post (Links to an external site.)
Kaggle Datasets (Links to an external site.)
UCI Machine Learning Repository (Links to an external site.)
VisualData (Links to an external site.)
PathMind Open-Datasets (Links to an external site.)
CIFAR-10 dataset (Links to an external site.)
IMDB Movie Reviews (Links to an external site.)
Google Research Datasets (Links to an external site.)
Keep in mind that some datasets may need to be processed before you can use them in learning projects–based on your own coding skills, you may want to target datasets that are more “ready-to-go”.
Project Proposal
Submit a pdf description of your proposed project (about 1-2 pages). Include the following sections:
Title: What is your project title?
Purpose: What problem are you trying to solve? What application or product are you trying to prototype? What do you expect to do in this project?
Method: What neural network method will you implement? What dataset will you use? What is the learning task? What are the data features? Are there classes? What existing project are you using on which to build your project?
Analysis: How will you assess the performance? What will use as a baseline? How will you visualize your results?
Project Milestone
This milestone is meant to validate you are making progress. Submit a pdf report (around 3 pages) written as an early draft of your final report, including:
What have you done so far?
What dataset are you using? Does your data need data cleaning or preprocessing? If so, what?
What were the results of your sanity-check model training run (on a limited dataset) to make sure you have enough computing resources to finish on time when you use the full dataset?
Are there any untested assumptions or other reasons that would prevent you from completing your project?
What are your next steps?
What is left to do?
Please use the sections of the final report format (below).
Final Project Report
Please include the following labeled sections:
Title: What is the title of your project?
Description: What is the problem you are trying to solve? What is your dataset or environment? What neural network model or approach are you using to solve your problem?
Method: What neural network method did you implement? What was the learning task? What dataset did you use? Did your dataset require cleaning or preprocessing? What are the data features? Classes? What existing project are you using on which to build your project?
Analysis: Include an analysis component. Consider the following questions: How does your project compare to other baselines? What is your classification accuracy (training/test)? What factors or variables are most critical in affecting your project’s performance? Include at least one graph or figure to visualize your results.
Due Diligence: Based on the results of this project (your pilot project, your prototype, etc), from a technical leadership point of view, what are your conclusions or recommendations for continuing this project in terms of scaling it up, using larger datasets, etc? How do your project’s result compare with your competitors or with state-of-the-art results? How would you assess the innovativeness of your project? Set your project within the larger AI/society space. Are there any ethical/privacy issues with your project, especially if it were scaled up, made public, etc? Are there any technical or platform concerns? Any patent/licensing concerns?
Conclusions: Your final summary of this project. Based on your experience and results, what is the next step you would recommend to take this project to the next level/phase?
Length: Minimum 6 pages, Maximum 10 pages. 11 point font, single space, 1-inch margins. Place citations and figures in an appendix – these pages do not count towards your min/max quota. Please label all figures/images.
Final Project Submission
Along with a pdf of your project report, include a zip of all files needed to run your project, including any packages not able to be installed via pip install. Include a README.txt file with any needed instructions to install/run your code. Eg, I need to be able to run your code like this: `python foo.py`.

How to create Testimonial Carousel using Bootstrap5

Clients' Reviews about Our Services