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A curated list of links to sources of latest updates in data/ml/ai
https://github.com/getindata/awesome-getindata-recommended-sources

List: awesome-getindata-recommended-sources

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A curated list of links to sources of latest updates in data/ml/ai

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# Awesome GetInData Recommended Sources [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)



> A curated list of links to sources of latest updates in data/ml/ai



## Contents



- [Podcasts](#podcasts)

- [Newsletters](#newsletters)

- [Youtube](#youtube)

- [Books](#books)

- [Learning-Platforms](#learning-platforms)

- [Blogs](#blogs)



## Podcasts



- [Radio DaTa](https://shows.acast.com/radio-data) - conversations with invited guests how data, cloud, analytics, and AI/ML/BI are used in their companies and general data-related eposodes by different hosts from [GetInData](https://getindata.com)

- [Data Engineering Podcast](https://www.dataengineeringpodcast.com/) - interviews with creators of data products and companies using these, sometimes panel discussions, hosted by Tobias Macey, 2 episodes per week

- [Kubernetes Podcast](https://kubernetespodcast.com/) - news from k8s world, followed by interviews with experts from the field

- [Stack Overflow Podcast](https://stackoverflow.blog/podcast/) - trening topics from IT world, including a lot of updates on AI

- [The Artificial Intelligence After Work Podcast](https://aiawpodcast.com/) - a live streamed long format conversation aiming to demystify data innovation and AI with invited guests from various companies

- [Data Sceptic](https://open.spotify.com/show/1BZN7H3ikovSejhwQTzNm4) - everything around the data, ml, de, se.



## Newsletters



- [DATA Pill](https://datapill.tech/) - blogposts, youtube videos and podcasts episodes on cloud, data and ml, carefully curated by [GetInData](https://getindata.com)

- [The Overflow](https://stackoverflow.blog/newsletter/) - stackoverflow blog, stackexchange questions (not only IT!) and interesting links from the web

- [Hackster](https://www.hackster.io/newsletter/sign_up) - electronics and IoT oriented, with a bit of AI and ML-on-edge



## Youtube



- [Sentdex](https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ) Evrything around Python

- [TheSeattleDataGuy](https://www.youtube.com/c/SeattleDataGuy?app=desktop) Data engineering

- [AdamMarczak](https://www.youtube.com/c/Azure4Everyone) Azure

- [MartinKleppmann](https://www.youtube.com/channel/UClB4KPy5LkJj1t3SgYVtMOQ) Great source of distributed systems, it's worth to find any talk given by him.

- [TechWorldwithNana](https://www.youtube.com/c/TechWorldwithNana) Everything about technologies

- [EngineerMan](https://www.youtube.com/c/EngineerMan) Everything about tech, hands on code examples. Interesting use cases.

- [thenewboston](https://www.youtube.com/user/thenewboston) Around many technologies, frameworks and languages.



## Learning-Platforms



- [ACloudGuru](https://acloudguru.com/) - Cloud, K8s, Linux. Sandbox environments is a plus.



## Books



- [Designing Data intensive applications](https://www.amazon.pl/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321) - Great source of internals of distributed systems. Written By Martin Kleppmann, also reccomend his. Transactions, replicas, partitioning, data streaming and more interesting topics.

- [Data management At Scale](https://www.amazon.pl/Data-Management-Scale-Enterprise-Architecture/dp/149205478X) - Good book about managing data in organization, small references about Data Mesh paradigm and avoding Data silos.

- [Streaming systems](https://www.amazon.pl/Streaming-Systems-Where-Large-Scale-Processing/dp/1491983876) - Created by Tyler Akidau, PMC member of Apache Beam project, one of the must read books for stream processing people.

- [Stream processing with apache Flink](https://www.amazon.pl/Stream-Processing-Apache-Flink-Implementation/dp/149197429X) - Created by coauthors of Apache Flink, Flink APIs maybe are a little bit stale but still worth to read about stream processing (great intro) and also Apache Flink internals.

- [Learning Spark 2nd edition](https://www.amazon.pl/Learning-Spark-Lightning-fast-Data-Analytics/dp/1492050040) - Great book to read more about Apache spark

- [Apache Kafka the definitive guide](https://www.confluent.io/resources/kafka-the-definitive-guide-v2/) You can get the book for free, it's everything about Apache Kafka

- [Building Event-Driven Microservices: Leveraging Organizational Data at Scale](https://www.amazon.pl/Building-Event-Driven-Microservices-Leveraging-Organizational/dp/1492057894). Great book about creating event driven applications/microservices.

- [Data Mesh](https://www.amazon.pl/Data-Mesh-Delivering-Data-Driven-Value/dp/1492092398) - Book written by author of Data Mesh paradigm. 

- [Foundations of Scalable Systems: Designing Distributed Architectures](https://www.amazon.pl/Foundations-Scalable-Systems-Distributed-Architectures/dp/1098106067) It's on my list to read

- [Cloud Native DevOps with Kubernetes: Building, Deploying, and Scaling Modern Applications in the Cloud](https://www.amazon.pl/Cloud-Native-DevOps-Kubernetes-Applications/dp/1098116828) Great book about k8s to understand core concepts.



## Blogs



List of People to follow recommended by Benjamin Rogojan, original link https://www.linkedin.com/feed/update/urn:li:activity:6979169467838652416?updateEntityUrn=urn%3Ali%3Afs_feedUpdate%3A%28V2%2Curn%3Ali%3Aactivity%3A6979169467838652416%29



- [Chip Huyen](https://huyenchip.com/blog/) Machine learning, data and AI.

- [Vicki Boykis](https://vickiboykis.com/) Data engineering and cloud.

- [Ananth P](https://www.dataengineeringweekly.com/) Data engineering.

- [Chris Riccomini](https://cnr.sh/essays/) Data engineering.

- [Christophe Blefari](https://www.blef.fr/author/christopheblefari/) Updates arround the data engineering area.

- [Alexey Grigorev](https://datatalks.club/) Everything around data space, you can subscribe on newsletter.

- [Chad Sanderson](https://dataproducts.substack.com/) Brandly new, data modelling, data quality etc. You can subscribe to newsletter.

- [Benn Stancil](https://benn.substack.com/) Data engineering and data area, you can subscribe to newsletter.

- [Barr Moses](https://barrmoses.medium.com/) Data stuff, data lineage, data quality, data as a product etc.

- [Daniel Beach](https://www.confessionsofadataguy.com/) Data engineering stuff but broadly, even geospatial is included.

- [Joseph M](https://www.startdataengineering.com/) Data engineering but mainly explaining concepts, good starting point.



## Contribute



Contributions welcome! Read the [contribution guidelines](contributing.md) first.