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scratch-implementation

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Natural Language Processing Nanodegree from Udacity Platform, in which I implement Hidden Markov Model for POS Tagger, Bidirectional LSTM for English-French Machine Translation, and End-to-End LSTM-based Speech Recognition

  • Updated Jun 26, 2018
  • Jupyter Notebook

Implementing most important basic building blocks of Deep Learning from scratch. My goal is to provide high quality Scratch Implementations of the fundamentals of Deep Learning and its applications, with interactive well documentated jupyter notebooks. All notebooks come along with implementations using Tensorflow, MXNet and Pytorch.

  • Updated Jul 1, 2020
  • Jupyter Notebook

A paper implementation and tutorial from scratch combining various great resources for implementing Transformers discussesd in Attention in All You Need Paper for the task of German to English Translation.

  • Updated Jun 22, 2021
  • Jupyter Notebook

This is my first Deep Learning project, which is a MNIST hand-written digits classifier. The model is implemented completely from scratch WITHOUT using any prebuilt optimization like Tensorflow or Pytorch. Tensorflow is imported only to load the MNIST data set. This model also uses 2 hidden layers with Adaptive Moment Optimization (Adam) and Dro…

  • Updated Jun 13, 2020
  • Jupyter Notebook

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