Project 3

	A	B	C	D	E	F	G
1	CS 5/7394 - Spring 2022	Due Date:	April 11, 2022 by 11:59pm.
2	Project 3
3		Uber Fares Dataset	How Many Upvotes	Reddit Popularity	Wake County Real Estate Prices	Fashion MNIST	CIFAR-10
4	Clean the Data (deal with missing values)
5	Use an Ordinal Encoder
6	Use a One Hot Encoder
7	Implement a custom transformer
8	Scale/normalize/standardize features using sklearn.preprocessing
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10	Use SGDClassifier
11	Use sklearn.linear_model.LinearRegression
12	Use sklearn.tree.DecisionTreeRegressor
13	Use sklearn.ensamble.RandomForestClassifier
14	Use sklearn.neighbors.KNeighborsClassifier
15	use OvO or OvR classifier
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17	Use k-fold Cross Validation (cross_val_score)
18	Use StratifiedKFold cross validation
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20	Use sklearn.metrics.mean_squared_error and at least one other sklearn.metrics option to evaluate model performance
21	Generate a confusion matrix
22	Generate a ROC Curve or related
23	Use Grid Search CV or RandomizedSearch CV to tune hyperparameters for a model
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25	Use an Ensamble of Methods
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27	Evaluate your system on the Test Data
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29	Create a single pipeline that does full process from data preparation to final prediction.
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35	Data Set Links:
36						Min tasks for a dataset:	5 tasks
37	Uber Fares Dataset	https://www.kaggle.com/datasets/yasserh/uber-fares-dataset				5394	Min 2 datasets
38	How Many Upvotes	https://www.kaggle.com/datasets/umairnsr87/predict-the-number-of-upvotes-a-post-will-get				7394	Min 3 datasets
39	Reddit Popularity	https://www.kaggle.com/datasets/kashyapgohil/predicting-reddit-post-popularity-through-comments
40	Wake County Real Estate Price Prediction	https://www.kaggle.com/datasets/nkanda/wake-county-housing-nc?select=WakeCountyHousing.csv
41	Fashion MNIST	https://github.com/zalandoresearch/fashion-mnist
42	CIFAR-10	http://www.cs.toronto.edu/~kriz/cifar.html
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