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data-cleaning-and-scraping-30days icon data-cleaning-and-scraping-30days

Just finished my 100 days challenge on machine learning and feel like I need to review and actually get hands on cleaning data. This challenge will (hopefully) also contains some real world data scraping and cleaning.

datasets icon datasets

Machine learning datasets used in tutorials on MachineLearningMastery.com

days-on-jupyter icon days-on-jupyter

使用 Jupyter 的零散心得, 練習, 試驗, 還有小小的 projects。

deepctr icon deepctr

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

deepface icon deepface

A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

django-locallibrary-tutorial icon django-locallibrary-tutorial

Local Library website written in Django; example for the MDN server-side development Django module: https://developer.mozilla.org/en-US/docs/Learn/Server-side/Django.

documentner icon documentner

Extract text data from documents using OCR (optical character recognition) technology and NER (named entity recognition).

drl icon drl

Deep Reinforcement Learning

easy-rl icon easy-rl

强化学习中文教程(蘑菇书),在线阅读地址:https://datawhalechina.github.io/easy-rl/

end-to-end-time-series icon end-to-end-time-series

This repository hosts code for my Time Series videos part of playlist here - https://www.youtube.com/playlist?list=PL3N9eeOlCrP5cK0QRQxeJd6GrQvhAtpBK

etl-data-pipelines-data-warehousing-business-intelligence- icon etl-data-pipelines-data-warehousing-business-intelligence-

This project challenged us to process and integrate data coming in from a variety of sources - IMDb data, movie rating data from MovieLens, and The Numbers data. We utilized multiple features of the Talend and SQL server to optimize the complete ETL process We then visualized the integrated data from our dimensional model in #Tableau and #PowerBI dashboards showcasing some core KPIs and metrics. This project helped us understand the various challenges faced while building data integration pipelines and business intelligence applications.

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