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update docs version of bulldozer project
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mrdbourke committed Oct 30, 2024
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" <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
"</a>\n",
"\n",
"[View source code](https://github.com/mrdbourke/zero-to-mastery-ml/blob/master/section-3-structured-data-projects/end-to-end-bluebook-bulldozer-price-regression-v2.ipynb) | [Read notebook in online book format](https://dev.mrdbourke.com/zero-to-mastery-ml/end-to-end-bluebook-for-bulldozers-price-regression-v2.ipynb)"
"[View source code](https://github.com/mrdbourke/zero-to-mastery-ml/blob/master/section-3-structured-data-projects/end-to-end-bluebook-bulldozer-price-regression-v2.ipynb) | [Read notebook in online book format](https://dev.mrdbourke.com/zero-to-mastery-ml/end-to-end-bluebook-for-bulldozers-price-regression-v2/)"
]
},
{
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"\n",
"There are several encoders available for different use cases.\n",
"\n",
"TK - does this table show up?\n",
"\n",
"| **Encoder** | **Description** | **Use case** | **For use on** |\n",
"|:-------------|:-----------------|:--------------|:----------------|\n",
"| [LabelEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html#sklearn.preprocessing.LabelEncoder) | Encode target labels with values between 0 and n_classes-1. | Useful for turning classification target values into numeric representations. | Target labels. |\n",
"| [OneHotEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html#onehotencoder) | Encode categorical features as a [one-hot numeric array](https://en.wikipedia.org/wiki/One-hot). | Turns every positive class of a unique category into a 1 and every negative class into a 0. | Categorical variables/features. |\n",
"| [OrdinalEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html#ordinalencoder) | Encode categorical features as an integer array. | Turn unique categorical values into a range of integers, for example, 0 maps to 'cat', 1 maps to 'dog', etc. | Categorical variables/features. |\n",
"| [TargetEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.TargetEncoder.html#targetencoder) | Encode regression and classification targets into a shrunk estimate of the average target values for observations of the category. Useful for converting targets into a certain range of values. | Target variables. |\n",
"| Encoder | Description | Use case | For use on |\n",
"| ----- | ----- | ----- | ----- |\n",
"| [`LabelEncoder`](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html#sklearn.preprocessing.LabelEncoder) | Encode target labels with values between 0 and n_classes-1. | Useful for turning classification target values into numeric representations. | Target labels. |\n",
"| [`OneHotEncoder`](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html#onehotencoder) | Encode categorical features as a [one-hot numeric array](https://en.wikipedia.org/wiki/One-hot). | Turns every positive class of a unique category into a 1 and every negative class into a 0. | Categorical variables/features. |\n",
"| [`OrdinalEncoder`](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html#ordinalencoder) | Encode categorical features as an integer array. | Turn unique categorical values into a range of integers, for example, 0 maps to 'cat', 1 maps to 'dog', etc. | Categorical variables/features. |\n",
"| [`TargetEncoder`](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.TargetEncoder.html#targetencoder) | Encode regression and classification targets into a shrunk estimate of the average target values for observations of the category. | Useful for converting targets into a certain range of values. | Target variables. |\n",
"\n",
"For our case, we're going to start with `OrdinalEncoder`.\n",
"\n",
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"\n",
"Let's now try it on a custom sample.\n",
"\n",
"Again, like all good machine learning cooking shows, I've searched the internet for \"bulldozer sales in America\" and [found a sale from 6th July 2024](https://www.purplewave.com/auction/240606/item/EK8504/2004-Caterpillar-D6R_XL-Crawlers-Crawler_Dozer-Missouri) (I'm writing these materials in mid 2024 so if it's many years in the future and the link doesn't work, check out the screenshot below). \n",
"\n",
"TK - image of bulldozer (add raw GitHub link from master)\n",
"Again, like all good machine learning cooking shows, I've searched the internet for \"bulldozer sales in America\" and [found a sale from 6th July 2024](https://www.purplewave.com/auction/240606/item/EK8504/2004-Caterpillar-D6R_XL-Crawlers-Crawler_Dozer-Missouri) (I'm writing these materials in mid 2024 so if it's many years in the future and the link doesn't work, check out the screenshot below).\n",
"\n",
"| <img src=\"https://github.com/mrdbourke/zero-to-mastery-ml/blob/updates-for-2025/images/structured-data-custom-bulldozer-advertisement.png?raw=true\" alt=\"Image of a 2004 Caterpillar D6R XL dozer from an online auction listing. The dozer is yellow, has an enclosed cab with AC and heat, and a large front blade. Key specs shown include 11,770 hours, a Caterpillar C9 diesel engine, and joystick steering. Tracks are 22 inches wide with single grouser pads. The contract price is $72,600.\" width=750/> | \n",
"| <img src=\"https://github.com/mrdbourke/zero-to-mastery-ml/blob/master/images/structured-data-custom-bulldozer-advertisement.png?raw=true\" alt=\"Image of a 2004 Caterpillar D6R XL dozer from an online auction listing. The dozer is yellow, has an enclosed cab with AC and heat, and a large front blade. Key specs shown include 11,770 hours, a Caterpillar C9 diesel engine, and joystick steering. Tracks are 22 inches wide with single grouser pads. The contract price is $72,600.\" width=750/> | \n",
"|:--:| \n",
"| Screenshot of a bulldozer sale advertisement. I took information from this advertisement to create our own custom sample for testing our machine learning model on data from the wild. [Source](https://www.purplewave.com/auction/240606/item/EK8504/2004-Caterpillar-D6R_XL-Crawlers-Crawler_Dozer-Missouri). |\n",
"\n",
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