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2016ccf_bdci_sougou

【源码以及PPT分享】2016CCF大数据与计算智能大赛：精准营销中搜狗用户画像挖掘

awesome-nlp-sentiment-analysis

:book: 收集NLP领域相关的数据集、论文、开源实现，尤其是情感分析、情绪原因识别、评价对象和评价词抽取方面。

awesome-recsys

Must-read papers on recommendation systems (RecSys)

bdci_car_2018

BDCI 2018 汽车行业用户观点主题及情感识别 决赛一等奖方案

bert_fun

captchaproject

CaptchaProject: Captcha Maker, Captcha recognition

chatglm-finetuning

基于ChatGLM-6B、ChatGLM2-6B、ChatGLM3-6B模型，进行下游具体任务微调，涉及Freeze、Lora、P-tuning、全参微调等

chinese-llama-alpaca

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

chinese-llama-alpaca-2

中文LLaMA-2 & Alpaca-2大模型二期项目 + 64K超长上下文模型 (Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models)

chinese_keyphrase_extractor

A tool for chinese keyphrase extraction 一个快速从自然语言文本中提取和识别关键短语的工具

competition-baseline

数据科学竞赛各种baseline代码、思路分享

crawler

Novel Crawler

ctr_model_zoo

some ctr model, implemented by PyTorch, such as Factorization Machines, Field-aware Factorization Machines, DeepFM, xDeepFM, Deep Interest Network

ctr_prediction

CTR prediction using FM FFM and DeepFM

customer_segments

Udacity_MachineLearning_P3

deepctr

Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

deepmatch

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors for user and item which can be used for ANN search.

designpattern

GOF23

dlnd_face_generation

DLND_P5

dnld_image_classifcation

elasticsearch-spark-recommender

Use Jupyter Notebooks to demonstrate how to build a Recommender with Apache Spark & Elasticsearch

finding_donors

Udacity_MachineLearning_P2

first_neural_network

udacity/DLND_P1

geektime-elk

ELK Training

gym

A toolkit for developing and comparing reinforcement learning algorithms.

interview-code-practice-python

面试题

jd_generation

generate JD automatically

kaggle_pbr

My best submission to the Kaggle competition "Predicting a Biological Response", ranked 17th over 711 teams.

kaggle_public

阿水的数据竞赛开源分支

kddcup-2020

2020-KDDCUP，Debiasing赛道 第6名解决方案