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Datasets:
FaiyazAzam
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hw1-tabular-ds-cars

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CarModel
stringlengths
12
33
Year
int64
2.01k
2.03k
Mileage
float64
0
161k
EngineSize
float64
1.5
6.4
Doors
int64
2
4
Price
float64
3.5k
180k
Jeep Wrangler Unlimited Sahara
2,022
32,582
2
4
32,991
Dodge Charger Scat Pack
2,021
46,396
6.4
4
37,895
Nissan Sentra SV
2,023
21,704
2
4
18,495
Hyundai Elantra N
2,025
8
2
4
35,623
Kia Forte LXS
2,021
35,256
2
4
15,795
Honda Accord Sport
2,020
41,457
1.5
4
23,155
Toyota Camry SE
2,023
19,129
2.5
4
26,064
Jeep Wagoneer
2,024
27,068
3
4
46,250
Jeep Grand Cherokee
2,022
14,475
3.6
4
30,195
Nissan Armada SL
2,025
0
3.5
4
61,644
Nissan Rogue SL
2,021
31,436
2.5
4
25,989
Chevrolet Suburban LT
2,021
56,549
5.3
4
41,994
BMW 1 Series 128i Coupe
2,008
160,500
3
2
3,500
Dodge Challenger GT
2,023
17,993
3.6
2
27,895
Porsche 718 Cayman GT4 RS
2,024
6,776
4
2
180,000
INFINITI G37 Journey
2,010
99,373
3.6
2
12,250
Ford Mustang Coupe
2,025
4
2.3
2
32,109
Chevrolet Corvette Stingray
2,022
10,939
6.2
2
59,916
Honda Fit EX
2,020
49,821
1.5
4
18,887
Toyota Corolla SE
2,023
10,447
2
4
23,900
Audi A7 3.0T Prestige
2,018
76,746
3
4
22,992
MAZDA MAZDA3 s
2,024
27,085
2.5
4
21,899
Hyundai Accent SE
2,016
54,190
1.6
4
7,995
Honda Civic Sport
2,025
2,604
2
4
26,908
Ford Mustang Convertible
2,017
97,976
3.7
2
15,995
McLaren MP4-12C Spider
2,013
19,404
3.8
2
114,999
MAZDA MX-5 Miata RF Grand Touring
2,025
0
2
2
39,739
BMW M4 Convertible
2,018
46,764
3
2
42,295
MINI Cooper S
2,019
51,641
2
2
19,604
Jaguar F-TYPE V8 S Convertible 2D
2,014
71,500
5
2
25,000

Dataset Card: [Cars-tabular]

Purpose

This dataset was created for educational purposes as part of a homework assignment.
It is intended to practice building, augmenting, and publishing datasets on the Hugging Face Hub.

Composition

  • Number of samples:
    • Original: N samples
    • Augmented: M samples
  • Features:
    • [list features/columns here, e.g. CarModel, Year, Mileage... or text, complexity_label... or image, has_groot]

Collection

  • Source:
    • Tabular (Cars): values manually collected from [source, e.g. online car listings or Google Sheets].
  • Size:
    • At least 30 original entries for tabular

Preprocessing & Augmentation

  • Preprocessing:
    • Cars: cleaned numeric + categorical values.
  • Augmentation techniques:
    • Tabular: Gaussian noise, sampling perturbations.

Labels

  • Cars: Target = Price (continuous).

Splits

  • original: manually collected data (30+).
  • augmented: synthetic data (300 for tabular).

Intended Use & Limitations

  • Use: Coursework, experimenting with dataset creation, augmentation, and Hugging Face tools.
  • Limits:
    • Not suitable for production ML training.
    • Synthetic samples may not represent real-world distributions.
    • Small dataset sizes → limited generalization.

Ethical Notes

  • No personally identifiable information (PII) or sensitive content.
  • Text is student-authored, not scraped.
  • Labels are for demonstration purposes only.

License

MIT License (for educational use).
(You can also set to cc-by-4.0 or apache-2.0 if required by your class.)

AI Usage Disclosure

  • No generative AI was used to produce original tabular; only augmentation steps.
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