tools like Matlab/Octave. If you are familiar with matrices, you can prove to yourself that the two forms are equivalent. While in the previous exercise you calculated J(θ) over a grid of θ0 and θ1 values

Limitations of Previous Methods • Illumination maps for natural images typically have relatively simple forms with known priors. • The model enables customizing the enhancement results by formulating constraints

Efficient Model Architectures & Layers Now we get to efficient model architectures and layers, which forms the crux of efficient deep learning. These are fundamental blocks that were designed from scratch

gains for ResNets and MobileNets. More recently, the researchers have started to combine these two forms to achieve both accuracy and latency gains. Weight Sharing using Clustering Recall that in quantization

us outperform baseline methods. Another example in this domain is the attention mechanism, which forms the backbone of the state of the art NLP model architectures such as the Transformer, which is now

models. The final english output along with the intermediate german text “Der Wal springt ins Wasser” forms a synthetic sample to train the forward model. Figure 3-12: An example of back-translation. EN=>DE