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Deep-Learning-Developer-Projects-2

Project 1 : Dense Net.

Learning to perform addition operation using a fully-connected/dense neural network.

Project 2 : CNN

Classification on a Quickdraw dataset. Used a Inception module ConvNet coupled with SNN(Self-Normalising-Network) propety using SELU(Scaled Exponential Linear Units) as activations. Trained the inception modules from scratch.

Project 3 : RNNs

Sentiment Analysis on the imdb dataset. Trained both word embedding layer as well as a layer of GRU.

Project 4 : Speech Enhancement.

CNN+BiRNN on noisy speech. Future work: GANs

Project 5 : Gender Classification

Simple Conv and Dense layers works well. However, unable to generalise to different datasets. Future work : Explore Transfer learning to small datasets from other distributions.

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