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AutoSave off Project Proposal.docx v Design Layout References Mailings Review View Help Search Foxit PDF File Home Insert Draw X Impact (Body) 18 A A Aa AE Paste BIU x² A L A v Clipboard Paragraph Elena Zdravkoska EZ Comments Editing Share 8 Find Normal Strong EVENT HEven Replace Dictate Editor Add-ins Styles Select Editing Editor Add-ins PROJECT PROPOSAL Dataset: https://www.kaggle.com/datasets/mrsimple07/car-prices- prediction-data Project description: I chose this dataset so that I would be able to work on developing a predictive model for car prices estimation. I will be able to achieve developing the model by analyzing the features like make, model, mileage, condition so in the end that same model will predict the car's price. Approach: For my project, I plan to use linear regression and neural networks. I chose these two algorithms because in my opinion they will work the best for the project. Considering that linear regression is simple but effective for prediction of continuous values for example the car prices and it will provide me results that will be easy to understand, I will use it as the baseline model. On the other hand, the neural networks will help me, particularly the deep learning models to handle the complex patterns in the data which will help me with improving prediction accuracy. I will start with preprocessing the data, then I will split the dataset into training and testing sets. Next is training of both models, the linear regression as baseline and the neural networks to capture the complex patterns. After training them I will compare their performance. In the end I will choose the better model and try to improve it by deploying it with new and unseen data. I will be working in Python. Goal: Page 1 of 2 256 words English (United States) Accessibility: Investigate 76°F Partly cloudy Search My goal is to predict effectively car prices. I aim to achieve this by optimizing the algorithms that I chose and fine-tuning the model parameters. Focus ENG 12:52 PM 8/5/2024 50%

AutoSave off Project Proposal.docx v Design Layout References Mailings Review View Help Search Foxit PDF File Home Insert Draw X Impact (Body) 18 A A Aa AE Paste BIU x² A L A v Clipboard Paragraph Elena Zdravkoska EZ Comments Editing Share 8 Find Normal Strong EVENT HEven Replace Dictate Editor Add-ins Styles Select Editing Editor Add-ins PROJECT PROPOSAL Dataset: https://www.kaggle.com/datasets/mrsimple07/car-prices- prediction-data Project description: I chose this dataset so that I would be able to work on developing a predictive model for car prices estimation. I will be able to achieve developing the model by analyzing the features like make, model, mileage, condition so in the end that same model will predict the car's price. Approach: For my project, I plan to use linear regression and neural networks. I chose these two algorithms because in my opinion they will work the best for the project. Considering that linear regression is simple but effective for prediction of continuous values for example the car prices and it will provide me results that will be easy to understand, I will use it as the baseline model. On the other hand, the neural networks will help me, particularly the deep learning models to handle the complex patterns in the data which will help me with improving prediction accuracy. I will start with preprocessing the data, then I will split the dataset into training and testing sets. Next is training of both models, the linear regression as baseline and the neural networks to capture the complex patterns. After training them I will compare their performance. In the end I will choose the better model and try to improve it by deploying it with new and unseen data. I will be working in Python. Goal: Page 1 of 2 256 words English (United States) Accessibility: Investigate 76°F Partly cloudy Search My goal is to predict effectively car prices. I aim to achieve this by optimizing the algorithms that I chose and fine-tuning the model parameters. Focus ENG 12:52 PM 8/5/2024 50%

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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hey, i have to make this project but i am stuck. i have to work on kaggle with a chosen dataset. this is the project proporsal i have sent to the professor which includes the dataset link. i am a begginer and i cant find anyone to help me or information that i understand online to make the project. i would appreciate some help, it shpuld be really basic and addaptable for a very very begginer. any kind of help is appreciated. the project is for data mining and machine learning. I already have the project propoal, now I need the code in python that i have to execute using nejral networks and linear regression. The code can be veru very simple, because i am an ultimate begfiner. the link for the dataset is

https://www.kaggle.com/datasets/mrsimple07/car-prices-prediction-data

Please do mot use ai and if any part of the code are from the internet highligh them. It should be in python preferebly tried on kaggle just for esier understandimg. If you could also make the test and training sets more visually better with graphs and similar i would be infinitely grateful. Thabk you a lot.

AutoSave off Project Proposal.docx v Design Layout References Mailings Review View Help Search Foxit PDF File Home Insert Draw X Impact (Body) 18 A A Aa AE Paste BIU x² A L A v Clipboard Paragraph Elena Zdravkoska EZ Comments Editing Share 8 Find Normal Strong EVENT HEven Replace Dictate Editor Add-ins Styles Select Editing Editor Add-ins PROJECT PROPOSAL Dataset: https://www.kaggle.com/datasets/mrsimple07/car-prices- prediction-data Project description: I chose this dataset so that I would be able to work on developing a predictive model for car prices estimation. I will be able to achieve developing the model by analyzing the features like make, model, mileage, condition so in the end that same model will predict the car's price. Approach: For my project, I plan to use linear regression and neural networks. I chose these two algorithms because in my opinion they will work the best for the project. Considering that linear regression is simple but effective for prediction of continuous values for example the car prices and it will provide me results that will be easy to understand, I will use it as the baseline model. On the other hand, the neural networks will help me, particularly the deep learning models to handle the complex patterns in the data which will help me with improving prediction accuracy. I will start with preprocessing the data, then I will split the dataset into training and testing sets. Next is training of both models, the linear regression as baseline and the neural networks to capture the complex patterns. After training them I will compare their performance. In the end I will choose the better model and try to improve it by deploying it with new and unseen data. I will be working in Python. Goal: Page 1 of 2 256 words English (United States) Accessibility: Investigate 76°F Partly cloudy Search My goal is to predict effectively car prices. I aim to achieve this by optimizing the algorithms that I chose and fine-tuning the model parameters. Focus ENG 12:52 PM 8/5/2024 50%
Transcribed Image Text:AutoSave off Project Proposal.docx v Design Layout References Mailings Review View Help Search Foxit PDF File Home Insert Draw X Impact (Body) 18 A A Aa AE Paste BIU x² A L A v Clipboard Paragraph Elena Zdravkoska EZ Comments Editing Share 8 Find Normal Strong EVENT HEven Replace Dictate Editor Add-ins Styles Select Editing Editor Add-ins PROJECT PROPOSAL Dataset: https://www.kaggle.com/datasets/mrsimple07/car-prices- prediction-data Project description: I chose this dataset so that I would be able to work on developing a predictive model for car prices estimation. I will be able to achieve developing the model by analyzing the features like make, model, mileage, condition so in the end that same model will predict the car's price. Approach: For my project, I plan to use linear regression and neural networks. I chose these two algorithms because in my opinion they will work the best for the project. Considering that linear regression is simple but effective for prediction of continuous values for example the car prices and it will provide me results that will be easy to understand, I will use it as the baseline model. On the other hand, the neural networks will help me, particularly the deep learning models to handle the complex patterns in the data which will help me with improving prediction accuracy. I will start with preprocessing the data, then I will split the dataset into training and testing sets. Next is training of both models, the linear regression as baseline and the neural networks to capture the complex patterns. After training them I will compare their performance. In the end I will choose the better model and try to improve it by deploying it with new and unseen data. I will be working in Python. Goal: Page 1 of 2 256 words English (United States) Accessibility: Investigate 76°F Partly cloudy Search My goal is to predict effectively car prices. I aim to achieve this by optimizing the algorithms that I chose and fine-tuning the model parameters. Focus ENG 12:52 PM 8/5/2024 50%
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