shaktisd Goto Github PK

nlp-datasets

Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)

nlu_datasets_for_task_oriented_dialogue

datasets of natural language understanding and dialogue state tracking

nn-from-scratch

Implementing a Neural Network from Scratch

nnmodel

nre

Neural Relation Extraction, including CNN, PCNN, CNN+ATT, PCNN+ATT

ntgbtminer

A no thrills getblocktemplate Bitcoin miner, written in Python.

opencv_3_license_plate_recognition_python

programminginscala

Programming in Scala, 2nd edition Study Notes

prompt-engineering-guide

Guide and resources for prompt engineering

python_engineering_project

pytorch-deep-learning

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

pytorch-transformer

Attention is all you need implementation

question_generation

Neural question generation using transformers

rasa_nlu_datasets

Rasa NLU datasets

recursivenn

Tensorflow implementation of Recursive Neural Networks using LSTM units

reinforcement-learning-in-finance

Materials for blogs and conferences

rl_trading

rnn

sampleapplication

samplenlpappwithspringboot

sec-insights

A real world full-stack application using LlamaIndex

seq2seq_model_live

sequence-to-sequence-and-attention-from-scratch-using-tensorflow

Sequence to Sequence and attention from scratch using Tensorflow

services-engineering

A reading list for services engineering, with a focus on cloud infrastructure services

signal-1m-tools

sp500

Current and Historical Lists of S&P 500 components since 1996

talibpython

Python code samples using ta lib for trading strategies

tensorflow

Computation using data flow graphs for scalable machine learning

transformer-from-scratch

Well documented, unit tested, type checked and formatted implementation of a vanilla transformer - for educational purposes.

visual-word2vec

Word2Vec + Principal Component Analysis + Clustering for low-dimensional semantic representation of a set of words or compositional MWEs.