ai323 Goto Github PK

ai323

Config files for my GitHub profile.

avalanche-subnet-tutorial-contest

awesome-deep-trading

List of awesome resources for machine learning-based algorithmic trading

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

awesome-quant

**的Quant相关资源索引

awesome_time_series_in_python

This curated list contains python packages for time series analysis

calendar

iOS calendar component written in Swift

coursera-crypto1

Coursera Stanford Cryptography 1

coursera-cryptography1

Assignments for Coursera's Cryptography I course by Dan Boneh

cryptography-1

Offered by Stanford University through Coursera

cryptography-i

Cryptography-I is a 6-week course in Coursera By Stanford University

cryptography-i---stanford-coursera

Solutions to the problem sets of Stanford University's Cryptography I class on Coursera.

cryptohelper

Generic Cryptography code utils used on matasano cryptography challenges

cryptopals-challenges

Challenge accepted!

cvcalendar

A custom visual calendar for iOS 8+ written in Swift (2.0).

deep-learning-in-time-series

Deep learning in time series analysis

effectivetensorflow

TensorFlow tutorials and best practices.

entity-embedding-rossmann

graph_test

lstnet

models

Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型）

multivariate-time-series-forecast-using-seq2seq-in-tensorflow

nanyang

nmt

TensorFlow Neural Machine Translation Tutorial

prml

PRML algorithms implemented in Python

rossmann_tsa_forecasts

Time Series Analysis & Forecasting of Rossmann Sales with Python. EDA, TSA and seasonal decomposition, Forecasting with Prophet and XGboost modeling for regression.

rtb-papers

A collection of research and survey papers of real-time bidding (RTB) based display advertising techniques.

seq2seq-signal-prediction

Signal prediction with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow

stanford-cryptography

Programming assignments for Coursera Cryptography I by Stanford University

stanford-cs229

Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford