Yu-Long Tsai's repositories

High-Cardinality-Categorical-Featue-Handling

Use Neural Network embedding to extract information from high cardinality features to boost your model performance!

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pandas_101

Pandas 101 各題詳解,優化了可讀性,使用向量化,增加使用場景及實用技巧。

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CS239S_ML_System_Design

Yu Long's note about Stanford CS239S Machine Learning System Design

pyspark_101

Yu Long's note about spark and pyspark

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DataScience101

Yu Long's note about data science

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DataEngineering101

Yu Long's note about data engineering

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TSTAR_forum_crawling

從資料科學家的觀點學習爬蟲、資料庫、實作輿情資料爬取建置、每日更新。

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airflow_101

yulong's note about airflow

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airfly

Auto Generate Airflow's dag.py On The Fly

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cicd

Yu Long's note about CICD and DevOps

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cs246_mining_massive_datasets

yulong's note about cs246_mining_massive_datasets

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DeepCTR

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

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DeepMatch

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

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demo_airfly

Yu Long's note about airfly (generate dag.py on the fly)

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docker_cheatsheet

Yu Long's docker cheatsheet

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dsa_101

yu long's note about data structure and algorithm

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elastic_search_cheatsheet

elastic_search_cheatsheet

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fastapi_101

yu long's note about FastAPI

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jupyter_workstation

yu long's note about jupyter workstation

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multi-armed-bandits-for-recommendation-systems

implement basic and contextual MAB algorithms for recommendation system

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paper101

Yu Long's note about machine learning and deep learning

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php101

note about php

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python_best_practice_for_development

yulong's note about best practice for development using python

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ray101

Yu Long's note about Ray

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RecommendationSystem-Word2vec

Recommendation system for customers in an E-commerce site based on Word2Vec embeddings

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spotify_lib

using spotify webapi to create some interesting project

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SQL_for_Business_analytics

yulong's note about datacomp SQL courses, focus on Business_analytics domain

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statistics_101

yulong's note about statistics

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weekly_sharing_101

1 concept a week, become a better yourself.

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