1 مستودع
Modules that group batch normalization, dropout, and linear layers into a single configurable block.
Distinct from Linear Mixing Layers: Distinct from Linear Mixing Layers: groups normalization and dropout with linear transformations, not just tensor dimension mixing.
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This is a structured deep learning curriculum for programmers, delivered as a collection of Jupyter notebooks. It teaches the fundamentals of training neural networks for computer vision, natural language processing, tabular data analysis, and collaborative filtering using PyTorch and the fastai library. The course is designed to be hands-on, guiding learners from building a training loop from scratch to fine-tuning pretrained models for a variety of practical tasks. The curriculum distinguishes itself by covering the full lifecycle of a deep learning project, from data preparation and augmen
Provides linear block composers that group normalization, dropout, and linear layers for model construction.