Latent space

Q: How deeply does Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI cover latent space?

Defines encoder-decoder flow and distributional purpose, but stops short of latent-variable mathematics or detailed training mechanics.

As explained in Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI

A latent space is a lower-dimensional representation space in which a model encodes condensed information about observed data.

A latent space is a lower-dimensional representation where an encoder stores highly condensed information about observed data. In a variational autoencoder, a decoder expands that representation and reconstructs the original input. When compression and reconstruction work well, the latent space captures core distributional information that can support generating new data. section 2.3.3

Synthetic tabular data

A tabular workflow can fit SDV's TVAESynthesizer to the 1,000-row German Credit Risk dataset and sample 10,000 additional synthetic rows. The latent representation is the compressed intermediate state behind this generation process. section 2.3.3

How Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI covers it

Cover of Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI

liveBook manning.com

Read Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI on liveBook Get the book at manning.com

Also explained in

liveBook manning.com

Build a Text-to-Image Generator (from Scratch)A latent space is a lower-dimensional representation space in which encoded data is represented before decoding or further generation.
liveBook manning.com

Learn Generative AI with PyTorchA latent representation produced by the encoder and passed to the decoder for reconstruction or generation.
liveBook manning.com

Math and Architectures of Deep LearningA learned lower-dimensional representation of an input.
liveBook manning.com

Deep Learning with R, Third EditionA latent space is a vector representation space in which tokens are positioned so that geometric relationships encode learned semantic or contextual relationships.
liveBook manning.com

Inside Deep Learning: Math, Algorithms, ModelsA learned internal encoding of input data intended to preserve information useful for later use or understanding.
liveBook manning.com

Deep Learning with Python, Third EditionAn encoded internal representation in latent space that preserves the structure needed for generation or manipulation.
liveBook manning.com

Graph Neural Networks in ActionThe space of lower-dimensional representations produced by an encoder, with each point representing encoded information about an input.
liveBook manning.com

AI-Powered SearchA latent factor is a learned, lower-dimensional attribute inferred from data to represent an underlying pattern associated with users or items.
liveBook manning.com

Evolutionary Deep Learning: Genetic algorithms and neural networksA latent space is the multidimensional representation space in which an encoder places input data for decoding or generation.
liveBook manning.com

Optimization Algorithms: AI techniques for design, planning, and control problemsA latent space is a lower-dimensional representation space whose vectors encode information about observed data or structures.
liveBook manning.com

Outlier Detection in PythonA latent space is a lower-level representation space whose coordinates encode hidden factors or inputs associated with observations.
liveBook manning.com

Generative AI in ActionA latent space is a lower-dimensional representation space in which data items are encoded by features that capture meaningful structure and similarity.
liveBook manning.com

Sutskever's ListAn internal representation that encodes input information in a lower-dimensional or transformed latent space.
liveBook manning.com

Machine Learning Algorithms in DepthA latent space is the representational space of unobserved variables or encoded representations associated with observed data.
liveBook manning.com

Build AI-Enhanced Web AppsAn embedding space is a continuous mathematical space in which embeddings are positioned so that distances or relationships represent properties of the underlying data.
liveBook manning.com

Introduction to Generative AI, Second EditionA latent representation is a compressed numerical representation that captures patterns or characteristics of the original data.
liveBook manning.com

Machine Learning Platform EngineeringA latent space is a learned lower-dimensional representation space in which entities are positioned according to underlying characteristics inferred by a model.

Compare how 18 books explain latent space →

Related concepts

encoderproduced by · An encoder is a component that transforms input data into an encoded representation for subsequent processing, reconstruction, comparison, or transmission.
decodeused by · Decoding is the process of transforming an encoded or internal representation into an interpretable or target-form output.
generatorused by · A generator is a computational component or construct that produces data or values from inputs, representations, context, or specified constraints.
encodingproduced by · Encoding is the transformation of information into a representation defined by a scheme for storage, processing, transmission, or interpretation.
diffusion modelused by · A diffusion model is a generative model that learns to produce data by reversing a process that progressively adds noise to data.
image generationused by · Image generation is the computational creation of new images from learned models, input data, or specified conditions.

This explainer was generated by Manning's knowledge graph from the text of Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI. The section links point to the parts of the book it draws on.