evanimiya Goto Github PK

annotated-transformer-kr

annotated-transformer-kr

anomalydetection

Anomaly Detection with R

bert

TensorFlow code and pre-trained models for BERT

chartify

Python library that makes it easy for data scientists to create charts.

deeplearningtutorial

Deep Learning tutorial

eddiedaddy

elemnet

ElemNet is a 17-layered fully connected network for the prediction of formation energy (enthalpy) from elemental compositions only. This repository contains the model weights and a Jupiter notebook for making predictions using the ElemNet model.

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fastbook

Draft of the fastai book

feature-selector

Feature selector is a tool for dimensionality reduction of machine learning datasets

financedatareader

Financial data reader

gentrl

Generative Tensorial Reinforcement Learning (GENTRL) model

improved-gan

Code for the paper "Improved Techniques for Training GANs"

keras-idiomatic-programmer

Handbooks and Code Samples for Software Engineers wanting to learn the Keras Machine Learning framework

kobert

Korean BERT pre-trained cased (KoBERT)

lung-cancer

3차원 의료영상 데이터의 시각적 설명을 위한 3D LRP SW

orion

A machine learning library for detecting anomalies in signals.

plotneuralnet

Latex code for making neural networks diagrams

publicdatareader

Open Source Public Data Reader

pytorch-pretrained-bert

📖The Big-&-Extending-Repository-of-Transformers: Pretrained PyTorch models for Google's BERT, OpenAI GPT & GPT-2, Google/CMU Transformer-XL.

scattertext

Beautiful visualizations of how language differs among document types.

spacy

💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

viztech

Plotnine replication of Financial Times Visual Vocabulary; Inspired by Vega