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@astonzhang astonzhang released this 26 Jul 05:04
· 1757 commits to master since this release
v0.17.0
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Learn about vigilant mode.

Dive into Deep Learning is now available on arxiv!

Framework Adaptation

We have added TensorFlow implementations up to Chapter 11 (Optimization Algorithms).

Towards v1.0

The following chapters have been significantly improved for v1.0:

  • Optimization (the first 4 sections)
  • Computational Performance
  • Computer Vision
  • Natural Language Processing: Pretraining
  • Natural Language Processing: Applications

Finalized chapters are being translated into Chinese (d2l-zh v2)

Other Improvements

  • Add BLEU uniform weights from the original paper
  • Revise the normalization trick in LogSumExp
  • Revise data standardization
  • Prove convexity using second derivatives for one-dimensional and multi-dimensional cases
  • Improve d2l.train_2d function
  • Improve convergence analysis of Newton's method
  • Improve SGD convergence analysis for convex objectives 1
  • Improve Convergence Analysis for Convex Objectives
  • Reorganize comparisons of network partitioning, layer-wise partitioning, and data parallelism
  • Improve d2l.box_iou function
  • Improve the "Labeling Classes and Offsets" subsection
  • Add discussions of issues of non-maximum suppression
  • Reorganize multiscale anchor boxes and multiscale detection
  • Highlight layerwise representations via deep nets in multiscale object detection
  • Connect SSD downsampling blocks to VGG blocks
  • Refer to YOLO and a recent survey on object detection
  • Fix legend issues in Kaggle CIFAR-10 and ImageNet Dogs
  • Improve performance on the Kaggle small-scale CIFAR-10 dataset
  • Improve performance on the Kaggle small-scale ImageNet Dog dataset
  • Improve the function to build the mapping from RGB to class indices for VOC labels
  • Revise motivations for transposed convolution
  • Rewrite basic transposed convolution operation
  • Add relations between transposed convolution and regular convolution implementations
  • Improve explanations of the pretrained backbone for the fully convolutional network
  • Improve the output synthesized image of style transfer
  • Add d2l.show_list_len_pair_hist
  • Fix d2l.get_negatives
  • Improve efficiency of d2l.Vocab
  • Exclude unknown tokens when training word embeddings
  • Add self-supervised learning
  • Add discussions of self-supervised learning in NLP
  • Revise the notation table
Assets 4