Certificate in Feature Engineering: Actionable Knowledge
-- ViewingNowThe Certificate in Feature Engineering: Actionable Knowledge is a comprehensive course designed to equip learners with essential skills in feature engineering, a critical aspect of data science and machine learning. This certificate program emphasizes the importance of feature engineering in improving the performance of predictive models and unlocking valuable insights from data.
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โข Feature Engineering Fundamentals: Introduction to feature engineering, data preprocessing, and understanding data types.
โข Feature Selection Techniques: Feature selection methods, including filter, wrapper, and embedded methods.
โข Dimensionality Reduction: Overview of dimensionality reduction techniques, including Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE).
โข Feature Engineering for Time Series Data: Techniques for feature engineering with time series data, including lagged features and rolling statistics.
โข Feature Engineering for Text Data: Techniques for feature engineering with text data, including tokenization, lemmatization, and natural language processing (NLP).
โข Feature Engineering with Images: Techniques for feature engineering with image data, including image augmentation and convolutional neural networks (CNNs).
โข Upsampling and Downsampling Techniques: Techniques for handling imbalanced datasets, including upsampling and downsampling.
โข Feature Engineering for Tabular Data: Techniques for feature engineering with tabular data, including one-hot encoding and binning.
โข Synthetic Data Generation for Feature Engineering: Methods for generating synthetic data to augment existing datasets and improve feature engineering.
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