PyTorch

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

PyTorch is an open-source machine learning framework for tensor computation and neural-network development.

PyTorch is an open-source, low-level deep learning framework for tensor computation and neural-network development. For tabular problems, it can support models that predict outcomes such as whether an Airbnb listing price exceeds the median. section 8.1

PyTorch is especially prominent in research, while TensorFlow is used more frequently in industry. Its design aims to remain accessible without requiring a separate high-level API, although additional toolkits can simplify development. section 8.1 section 8.7

Common ways to work with PyTorch for tabular deep learning include:

• Use PyTorch directly when retaining control over the framework's distinctive code and model-building details matters. section 8.2
• Use fastai for a general-purpose, high-level PyTorch API and tabular-data workflows designed to define, train, and exercise models with few lines of code. section 8.1 section 8.7
• Use Lightning when the main need is to abstract the training loop, or Lightning Flash for rapid prototyping, baselining, fine-tuning, and tabular problems. section 8.1 section 8.7
• Consider PyTorch Tabular or PyTorch-compatible TabNet when selecting a specialized tabular-data library. section 8.7

Figure 8.3 Deep learning stacks for tabular data

Compare the framework and high-level API layers available for deep learning with tabular data. section 8.1

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

How deep it goes

Compares PyTorch's stack role and toolkit options, but defers detailed layer definitions and implementation mechanics.

Examples

Uses Airbnb NYC price classification and compares framework stacks for tabular deep learning.

What you can do after

Evaluate/understand PyTorch ecosystem choices for building deep-learning solutions to tabular-data problems.

How it connects

Connects PyTorch with TensorFlow, fastai, Lightning, Lightning Flash, TabNet, and PyTorch Tabular.

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Also explained in

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  Inside Deep Learning: Math, Algorithms, ModelsA Python deep learning library that provides tensor computation, automatic differentiation, and data abstractions for neural network training.
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  Deep Learning with R, Third EditionPyTorch is an open-source machine-learning library providing tensor computation and automatic differentiation capabilities.
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  Deep Learning with PyTorch, Second EditionThe PyTorch core Python library namespace that exposes tensor operations and functions such as mathematical elementwise operations.
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  Natural Language Processing in Action, Second EditionPyTorch is an open-source machine-learning framework for building and training neural-network models with tensor computation and automatic differentiation.
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  Deep Learning with Python, Third EditionA Python machine-learning library used here as one of the frameworks whose code can run element-wise operations on GPUs; only PyTorch is actually a library entry in the glossary, but the section groups it with JAX and TensorFlow as frameworks.
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  Learn Generative AI with PyTorchA deep learning library used here for building and training neural networks, especially with dynamic computation graphs and GPU acceleration.
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  Math and Architectures of Deep LearningAn open-source machine learning library used here to provide the chapter's executable code examples and automatic gradient computation.
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  Optimization Algorithms: AI techniques for design, planning, and control problemsPyTorch is an open-source machine-learning library that provides tensor computation and automatic differentiation for building and training neural networks.
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  Build a Large Language Model (From Scratch)The deep learning library used here to normalize attention scores along a specified tensor dimension with softmax.
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  Build a Reasoning Model (From Scratch)A deep learning library used here to represent tensors and define optimizers that minimize losses.

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Related concepts

• PyTorch Geometricused by · PyTorch Geometric is an open-source Python library that extends PyTorch with data structures and operators for graph and geometric machine learning.
• fastaiused by · fastai is a high-level deep learning library built on PyTorch that provides layered abstractions for model development.
• to methodhas part · The PyTorch to method moves a tensor or module to a specified device and can change its data type.
• GPU kerneluses · A GPU kernel is an executable program or function that performs computation on a graphics processing unit, commonly using parallel threads.

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.