This repo is a work in progress.
This will be a systematic introduction to Transformers with well chosen examples starting with basic concepts such as Back-propagation. We will dive into Sequential Models, looking into RNNs, LSTM models and Gated RNNs. We will wade through Latent Semantic Analsysis and will look more closely into the concept of Attention.
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Statistical Learning, Kernel Methods, Kolomogorov-Arnold Networks
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Deep Learning for solving Image Processing problems and Generative Tasks
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Hypothesis Testing, Estimation of Treatment Effects and Generalized Synthetic Control
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Queueing Networks, Queueing Theory, Reversible Stochastic Processes
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Spectral Analysis, Optimization in Spectral Domain, Spectral Domain Modeling
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Computability, Automata, Logic Systems, Formal Grammars and Theory of Parsing
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Thought Forming, Consciousness, Intelligent Machines, Semantic Inference
This repository uses git Large File Storage feature. In order to download locally the large files (> 1MB) which are maintained by git LFS you will need to install the Git extension for versioning large files: https://git-lfs.com/