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misc

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

model-deploy

Spark PMML 模型离线部署

neural-image-assessment

A PyTorch Implementation of Neural IMage Assessment

neural-image-assessment-1

Implementation of NIMA: Neural Image Assessment in Keras

neural_network_voices

This is the code for "Neural Network Voices" by Siraj Raval on Youtube

nima.pytorch

NIMA: Neural IMage Assessment

nl2sql

Text2SQL 语义解析数据集、解决方案、paper资源整合项目

nl2sql-1

Transform natural language queries to SQL

nl2sql_baseline

nlp

兜哥出品 <一本开源的NLP入门书籍>

nlp-models-tensorflow

Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

nlp-notebooks

A collection of notebooks for Natural Language Processing from NLP Town

nlp_for_korean

한국어 자연어처리를 위한 코드 정리

notebooks

Some sample IPython notebooks for scikit-learn

notebooks-1

Jupyter notebooks for the Natural Language Processing with Transformers book

nyoka

Nyoka is a Python library to export ML/DL models into PMML (PMML 4.4.1 Standard).

o2f

Convert observations to formulas, to reduce the time taken by researchers dealing with numerical computation

otmql4py

Open Trading Metatrader 4 Python Integration

paddleocr

Awesome multilingual OCR toolkits based on PaddlePaddle （practical ultra lightweight OCR system, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices）

paper-implementation-dstp-rnn-for-stock-prediction-based-on-da-rnn

基於DA-RNN之DSTP-RNN論文試做(Ver1.0)

pattern-recognition-for-forex-trading

http://pythonprogramming.net/machine-learning-pattern-recognition-algorithmic-forex-stock-trading/

pbdl-book

Welcome to the Physics-based Deep Learning Book (v0.2)

pcap_dnsproxy

A Full Backup from https://github.com/chengr28/Pcap_DNSProxy

personae

📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.

piecewise_segmentation_stock_price

Python code implementing the piecewise segmentation of a signal given in input. Three main algorithms (sliding windows, top down and bottom up) are implemented and compared

pipeline-ensemble-sklearn-classifiers

Use of sklearn and ensemble for supervised machine learning on counterfeit and anomalous data. Data sets provided.

pmml-parser

JPMML 加载 PMML 模型进行 predict

ppjutils

some usefult utils like change tools and city lon and lat

principles-zh

:book: 原则 · 中文版