This video covers the process of encoding tabular data to prepare it as a feature vector for a PyTorch neural network. Tabular data, characterized by its structured form with rows and columns akin to a spreadsheet, often needs preprocessing before being fed into a neural network. The video covers essential techniques such as standardization and normalization. Standardization involves transforming the features to have a mean of 0 and a standard deviation of 1, often using the z-score, to make the training process more efficient. Normalization scales the variables to fall within a specific range, such as 0 to 1, making the data uniform. The presenter also explores the creation of dummy variables, which are binary columns created to represent categorical variables, thereby converting non-numeric data into a format that can be provided to a neural network. This comprehensive tutorial provides both theoretical insights and hands-on coding examples to help viewers understand and apply these critical preprocessing steps. Code for This Video: https://github.com/jeffheaton/app_deep_learning/blob/main/t81_558_class_03_3_feature_encode.ipynb ~~~~~~~~~~~~~~~ COURSE MATERIAL ~~~~~~~~~~~~~~~ 📖 Textbook - Coming soon 😸🐙 GitHub - https://github.com/jeffheaton/app_deep_learning/ ▶️ Play List -    • 2023 PyTorch Version Applications of ...   🏫 WUSTL Course Site - https://sites.wustl.edu/jeffheaton/t81-558/ ~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~ 🖥️ Website: https://www.heatonresearch.com/ 🐦 Twitter - https://twitter.com/jeffheaton 😸🐙 GitHub - https://github.com/jeffheaton 📸 Instagram - https://www.instagram.com/jeffheatondotcom/ 🦾 Discord: https://discord.gg/3bjthYv ▶️ Subscribe: null ~~~~~~~~~~~~~~ SUPPORT ME 🙏~~~~~~~~~~~~~~ 🅿 Patreon - https://www.patreon.com/jeffheaton 🙏 Other Ways to Support (some free) - https://www.heatonresearch.com/support.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #PyTorch #NeuralNetworks #TabularData #DataPreprocessing #Standardization #Normalization #zscore #MachineLearning #FeatureEngineering #DummyVariables #AI #DeepLearning