+20 -19

Data/Machine Learning.md

reviewed

··· 21 21 22 22 ### Resources 23 23 24 24 - - [Applied ML in Production](https://madewithml.com/courses/applied-ml-in-production/). 25 25 - - [Applied ML](https://github.com/eugeneyan/applied-ml). 26 26 - - Microsoft [ML Model Production Checklist](https://microsoft.github.io/code-with-engineering-playbook/machine-learning/ml-model-checklist/) and [Fundamental Checklist](https://microsoft.github.io/code-with-engineering-playbook/machine-learning/ml-fundamentals-checklist/). 27 27 - - [Engineering best practices for Machine Learning](https://se-ml.github.io/practices/). 28 28 - - [Full Stack Deep Learning](https://course.fullstackdeeplearning.com/). 29 29 - - [Awesome Production Machine Learning](https://github.com/EthicalML/awesome-production-machine-learning). 30 30 - - [Awesome Machine Learning Engineer](https://github.com/radix-ai/awesome-machine-learning-engineer). 31 31 - - [Machine Learning Engineer Roadmap](https://github.com/chris-chris/ml-engineer-roadmap). 32 32 - - [Awesome MLOps](https://github.com/visenger/awesome-mlops).[Another awesome MLOps](https://github.com/kelvins/awesome-mlops). 33 33 - - [Made With ML](https://madewithml.com/). 34 34 - - [Scikit-Learn Related Projects](https://scikit-learn.org/stable/related_projects.html). 24 24 + - [Applied ML in Production](https://madewithml.com/courses/applied-ml-in-production/) 25 25 + - [Applied ML](https://github.com/eugeneyan/applied-ml) 26 26 + - Microsoft [ML Model Production Checklist](https://microsoft.github.io/code-with-engineering-playbook/machine-learning/ml-model-checklist/) and [Fundamental Checklist](https://microsoft.github.io/code-with-engineering-playbook/machine-learning/ml-fundamentals-checklist/) 27 27 + - [Engineering best practices for Machine Learning](https://se-ml.github.io/practices/) 28 28 + - [Full Stack Deep Learning](https://course.fullstackdeeplearning.com/) 29 29 + - [Awesome Production Machine Learning](https://github.com/EthicalML/awesome-production-machine-learning) 30 30 + - [Awesome Machine Learning Engineer](https://github.com/radix-ai/awesome-machine-learning-engineer) 31 31 + - [Machine Learning Engineer Roadmap](https://github.com/chris-chris/ml-engineer-roadmap) 32 32 + - [Awesome MLOps](https://github.com/visenger/awesome-mlops).[Another awesome MLOps](https://github.com/kelvins/awesome-mlops) 33 33 + - [Made With ML](https://madewithml.com/) 34 34 + - [Scikit-Learn Related Projects](https://scikit-learn.org/stable/related_projects.html) 35 35 - [Getting machine learning to production](https://vickiboykis.com/2020/06/09/getting-machine-learning-to-production/) 36 36 37 37 ## [Machine Learning Technical Debt](https://matthewmcateer.me/blog/machine-learning-technical-debt) ··· 45 45 46 46 ## Resources 47 47 48 48 - - [The Open-Source Data Science Masters](https://github.com/datasciencemasters/go). 49 49 - - [The Data Visualization Catalogue](https://datavizcatalogue.com/). 50 50 - - [Chart Dos and Don'ts](https://www.eea.europa.eu/data-and-maps/daviz/learn-more/chart-dos-and-donts). 51 51 - - [Machine Learning Tutorials](https://ujjwalkarn.github.io/Machine-Learning-Tutorials/). 52 52 - - [Data looks better naked](https://www.darkhorseanalytics.com/blog/data-looks-better-naked). 53 53 - - [Guides for Visualizing Reality](https://flowingdata.com/2020/06/01/guides-for-visualizing-reality/). 54 54 - - [Model Interpretability](https://ff06-2020.fastforwardlabs.com/). 55 55 - - [Diverse Counterfactuals](https://www.microsoft.com/en-us/research/blog/open-source-library-provides-explanation-for-machine-learning-through-diverse-counterfactuals/). 48 48 + - [The Open-Source Data Science Masters](https://github.com/datasciencemasters/go) 49 49 + - [The Data Visualization Catalogue](https://datavizcatalogue.com/) 50 50 + - [Visualization Curriculim](https://jjallaire.github.io/visualization-curriculum/) 51 51 + - [Chart Dos and Don'ts](https://www.eea.europa.eu/data-and-maps/daviz/learn-more/chart-dos-and-donts) 52 52 + - [Machine Learning Tutorials](https://ujjwalkarn.github.io/Machine-Learning-Tutorials/) 53 53 + - [Data looks better naked](https://www.darkhorseanalytics.com/blog/data-looks-better-naked) 54 54 + - [Guides for Visualizing Reality](https://flowingdata.com/2020/06/01/guides-for-visualizing-reality/) 55 55 + - [Model Interpretability](https://ff06-2020.fastforwardlabs.com/) 56 56 + - [Diverse Counterfactuals](https://www.microsoft.com/en-us/research/blog/open-source-library-provides-explanation-for-machine-learning-through-diverse-counterfactuals/)

+36 -34

Open Data.md

reviewed

··· 212 212 213 213 ## Open Datasets 214 214 215 215 - - [Wikipedia](https://dumps.wikimedia.org/). 216 216 - - [Github](https://www.gharchive.org/). 217 217 - - [HackerNews](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=hacker_news). 218 218 - - [Reddit](https://pushshift.io/). 219 219 - - [Blockchain](https://github.com/blockchain-etl). 220 220 - - [Our World In Data](https://github.com/owid/owid-datasets). 221 221 - - [Fivethirtyeight](https://data.fivethirtyeight.com/). 222 222 - - [BuzzFeed News](https://github.com/BuzzFeedNews). 223 223 - - [ProPublica](https://www.propublica.org/datastore/). 224 224 - - [World Bank](https://data.worldbank.org/indicator). 225 225 - - [Ecosyste.ms](https://repos.ecosyste.ms/open-data). An open API service providing repository metadata for many open source software ecosystems. 226 226 - - [Deps.dev](https://deps.dev/). 215 215 + - [Wikipedia](https://dumps.wikimedia.org/) 216 216 + - [Github](https://www.gharchive.org/) 217 217 + - [HackerNews](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=hacker_news) 218 218 + - [Reddit](https://pushshift.io/) 219 219 + - [Blockchain](https://github.com/blockchain-etl) 220 220 + - [Our World In Data](https://github.com/owid/owid-datasets) 221 221 + - [Fivethirtyeight](https://data.fivethirtyeight.com/) 222 222 + - [BuzzFeed News](https://github.com/BuzzFeedNews) 223 223 + - [ProPublica](https://www.propublica.org/datastore/) 224 224 + - [World Bank](https://data.worldbank.org/indicator) 225 225 + - [Ecosyste.ms](https://repos.ecosyste.ms/open-data) 226 226 + - [Deps.dev](https://deps.dev/) 227 227 228 228 ### Open Data Organizations 229 229 230 230 - [Datahub](https://datahub.io/) 231 231 + - [Frictionless](https://frictionlessdata.io/) 231 232 - [Open Data Services](https://opendataservices.coop) 232 233 - [Catalyst Cooperative](https://catalyst.coop/) 233 234 - [Carbon Plan](https://github.com/carbonplan) ··· 236 237 237 238 ### Indexes 238 239 239 239 - - [Google Dataset Search](https://datasetsearch.research.google.com/). 240 240 - - [BigQuery Public Data](https://cloud.google.com/bigquery/public-data). 241 241 - - [Kaggle Datasets](https://www.kaggle.com/datasets). 242 242 - - [Datahub](https://datahub.io/awesome). By [Datopian](https://tech.datopian.com/), makers of CKAN. 243 243 - - [HuggingFace Datasets](https://huggingface.co/datasets). 244 244 - - [Data World](https://data.world/datasets/open-data). 245 245 - - [Enigma](https://enigma.com/). 246 246 - - [DoltHub](https://www.dolthub.com/discover). 240 240 + - [Google Dataset Search](https://datasetsearch.research.google.com/) 241 241 + - [BigQuery Public Data](https://cloud.google.com/bigquery/public-data) 242 242 + - [Kaggle Datasets](https://www.kaggle.com/datasets) 243 243 + - [Datahub](https://datahub.io/awesome) 244 244 + - [HuggingFace Datasets](https://huggingface.co/datasets) 245 245 + - [Data World](https://data.world/datasets/open-data) 246 246 + - [Enigma](https://enigma.com/) 247 247 + - [DoltHub](https://www.dolthub.com/discover) 247 248 - [Socrata](https://dev.socrata.com/) 248 248 - - [Nasdaq](https://data.nasdaq.com/search). 249 249 - - [Zenodo](https://zenodo.org/search?page=1&size=20&q=&file_type=csv&type=dataset&sort=mostviewed). 250 250 - - [Splitgraph](https://www.splitgraph.com/explore). 251 251 - - [Awesome Public Datasets](https://github.com/awesomedata/awesome-public-datasets). 249 249 + - [Nasdaq](https://data.nasdaq.com/search) 250 250 + - [Zenodo](https://zenodo.org/search?page=1&size=20&q=&file_type=csv&type=dataset&sort=mostviewed) 251 251 + - [Splitgraph](https://www.splitgraph.com/explore) 252 252 + - [Awesome Public Datasets](https://github.com/awesomedata/awesome-public-datasets) 252 253 - [Data Packaged Core Datasets](https://github.com/datasets/) 253 253 - - [Internet Archive Dataset Collection](https://archive.org/details/datasets). 254 254 - - [AWS Open Data Registry](https://registry.opendata.aws/). 255 255 - - [Datamarket](https://en.datamarket.es/). 256 256 - - [Open Data Stack Exchange](https://opendata.stackexchange.com/). 257 257 - - [IPFS Datasets](https://awesome.ipfs.io/datasets/). 258 258 - - [Datasets Subreddit](https://www.reddit.com/r/datasets/). [Open Data Subreddit](https://www.reddit.com/r/opendata/). 259 259 - - [Academic Torrents Datasets](https://academictorrents.com/browse.php). 260 260 - - [Open Data Inception](https://opendatainception.io/). 261 261 - - [Victoriano's Data Sources](https://victorianoi.notion.site/Data-Sources-79b28912c6d941af99e6ef102c578fa0). 262 262 - - [Data is Plural](https://www.data-is-plural.com/). 254 254 + - [Internet Archive Dataset Collection](https://archive.org/details/datasets) 255 255 + - [AWS Open Data Registry](https://registry.opendata.aws/) 256 256 + - [Datamarket](https://en.datamarket.es/) 257 257 + - [Open Data Stack Exchange](https://opendata.stackexchange.com/) 258 258 + - [IPFS Datasets](https://awesome.ipfs.io/datasets/) 259 259 + - [Datasets Subreddit](https://www.reddit.com/r/datasets/). [Open Data Subreddit](https://www.reddit.com/r/opendata/) 260 260 + - [Academic Torrents Datasets](https://academictorrents.com/browse.php) 261 261 + - [Open Data Inception](https://opendatainception.io/) 262 262 + - [Victoriano's Data Sources](https://victorianoi.notion.site/Data-Sources-79b28912c6d941af99e6ef102c578fa0) 263 263 + - [Data is Plural](https://www.data-is-plural.com/) 264 264 + - [Public APIs](https://github.com/public-api-lists/public-api-lists) 263 265 264 266 ## Open Source Web Data IDE 265 267