Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) are powerful tools for sequential data learning, mimicking the persistent nature of human thoughts. These neural networks can be applied to various real-life applications such as time-series data prediction, text sequence processing,

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Graph Neural Networks (GNNs) are a versatile form of neural networks that encompass various network architectures like NNs, CNNs, and RNNs, as well as unsupervised learning models such as RBM and DBNs. They find applications in diverse fields such as object detection, machine translation, and drug d

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Explore the fundamentals of recurrent neural networks (RNNs) and convolutional neural networks (CNNs) in the context of downstream applications. Delve into LSTM, GRU, and RNN variants, alongside CNN architectures like ConvNext, ResNet, and more. Understand the mathematical formulations of RNNs and c

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This content delves into the concept of decoding in natural language generation (NLG) using RNN Encoder-Decoder models. It discusses decoding approaches such as greedy decoding, sampling from probability distributions, and beam search in RNNs. It also explores applications of decoding and machine tr

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Today's presentation will delve into the comparison between RNNs and CNNs for various tasks, discuss a state-of-the-art approach for Sequence Modelling, and explore augmented RNN models. The discussion will include empirical evaluations, baseline model choices for tasks like text classification and

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Explore the realm of Recurrent Neural Networks (RNNs), including Long Short-Term Memory (LSTM) models and sequence-to-sequence architectures. Delve into backpropagation through time, vanishing/exploding gradients, and the importance of modeling sequences for various applications. Discover why RNNs o

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Explore the basics of Recurrent Neural Networks (RNNs) including the Vanilla RNN unit, LSTM unit, forward and backward passes, LSTM variants like Peephole LSTM and GRU. Dive into detailed illustrations and considerations for tasks like translation from English to French. Discover the inner workings

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This presentation delves into the intricacies of Neural Image Captioning, focusing on a model known as Neural Image Caption (NIC). The NIC's primary goal is to automatically generate descriptive English sentences for images. Leveraging the Encoder-Decoder structure, the NIC uses a deep CNN as the en

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