Cookbook
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Superset | 52,351 |  | 2 | 10 hours ago | 3 | April 29, 2022 | 1,350 | apache-2.0 | TypeScript | |
| Apache Superset is a Data Visualization and Data Exploration Platform | ||||||||||
| Cookbook | 11,769 | 2 months ago | 110 | apache-2.0 | ||||||
| The Data Engineering Cookbook | ||||||||||
| Every Single Day I Tldr | 304 | 8 days ago | ||||||||
| A daily digest of the articles or videos I've found interesting, that I want to share with you. | ||||||||||
| Waimak | 73 | 1 | 1 | 6 months ago | 31 | August 16, 2021 | 12 | apache-2.0 | Scala | |
| Waimak is an open-source framework that makes it easier to create complex data flows in Apache Spark. | ||||||||||
| Ml In Production | 39 | 7 months ago | 12 | mit | Python | |||||
| The practical use-cases of how to make your Machine Learning Pipelines robust and reliable using Apache Airflow. | ||||||||||
| Big Data Engineering Indonesia | 18 | 3 years ago | ||||||||
| A curated list of big data engineering tools, resources and communities. | ||||||||||
| Awesome Dataops | 10 | a year ago | cc0-1.0 | |||||||
| Awesome list of dataops products, open source and resources | ||||||||||
| Sparkitecture | 9 | 2 years ago | gpl-3.0 | |||||||
| A collection of “cookbook-style” scripts for simplifying data engineering and machine learning in Apache Spark. | ||||||||||
| Docker Streamsets Kafka Minecraft | 7 | 5 years ago | Shell | |||||||
| Visualize Apache logs in Minecraft using Docker, Streamsets Data Collector, Spigot and Kafka . | ||||||||||
| Awesome Data Science And Engineering | 4 | 4 years ago | mit | |||||||
| A curated list of Data Science and Engineering frameworks, tools, libraries and related list of tutorials. | ||||||||||
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Contents:
- Introduction
- Basic Engineering Skills
- Advanced Engineering Skills
- Hands On Course‚
- Case Studies
- Best Practices Cloud Platforms
- 130+ Data Sources Data Science
- 1001 Interview Questions
- Recommended Books, Courses, and Podcasts
Full Table Of Contents:
Introduction
- What is this Cookbook
- Data Engineer vs Data Scientist
- My Data Science Platform Blueprint
- Who Companies Need
Basic Engineering Skills
- Learn To Code
- Get Familiar With Git
- Agile Development
- Software Engineering Culture
- Learn how a Computer Works
- Data Network Transmission
- Security and Privacy
- Linux
- Docker
- The Cloud
- Security Zone Design
Advanced Engineering Skills
- Data Science Platform
- Connect
- Buffer
-
Processing Frameworks
- Lambda and Kappa Architecture
- Batch Processing
- Stream Processing
- Should You do Stream or Batch Processing
- Is ETL still relevant for Analytics?
- MapReduce
-
Apache Spark
- What is the Difference to MapReduce?
- How Spark Fits to Hadoop
- Spark vs Hadoop
- Spark and Hadoop a Perfect Fit
- Spark on YARn
- My Simple Rule of Thumb
- Available Languages
- Spark Driver Executor and SparkContext
- Spark Batch vs Stream processing
- How Spark uses Data From Hadoop
- What are RDDs and How to Use Them
- SparkSQL How and Why to Use It
- What are Dataframes and How to Use Them
- Machine Learning on Spark (TensorFlow)
- MLlib
- Spark Setup
- Spark Resource Management
- AWS Lambda
- Apache Flink
- Elasticsearch
- Apache Drill
- StreamSets
- Store
- Visualize
-
Machine Learning
- How to do Machine Learning in production
- Why machine learning in production is harder then you think
- Models Do Not Work Forever
- Where are The Platforms That Support Machine Learning
- Training Parameter Management
- How to Convince People That Machine Learning Works
- No Rules No Physical Models
- You Have The Data. Use It!
- Data is Stronger Than Opinions
- AWS Sagemaker
Hands On Course
- What We Want To Do
- Thoughts On Choosing A Development Environment
- A Look Into the Twitter API
- Ingesting Tweets with Apache Nifi
- Writing from Nifi to Apache Kafka
- Apache Zeppelin Data Processing
- Switch Processing from Zeppelin to Spark
Case Studies
- Data Science @Airbnb
- Data Science @Amazon
- Data Science @Baidu
- Data Science @Blackrock
- Data Science @BMW
- Data Science @Booking.com
- Data Science @CERN
- Data Science @Disney
- Data Science @DLR
- Data Science @Drivetribe
- Data Science @Dropbox
- Data Science @Ebay
- Data Science @Expedia
- Data Science @Facebook
- Data Science @Google
- Data Science @Grammarly
- Data Science @ING Fraud
- Data Science @Instagram
- Data Science @LinkedIn
- Data Science @Lyft
- Data Science @NASA
- Data Science @Netflix
- Data Science @OLX
- Data Science @OTTO
- Data Science @Paypal
- Data Science @Pinterest
- Data Science @Salesforce
- Data Science @Siemens Mindsphere
- Data Science @Slack
- Data Science @Spotify
- Data Science @Symantec
- Data Science @Tinder
- Data Science @Twitter
- Data Science @Uber
- Data Science @Upwork
- Data Science @Woot
- Data Science @Zalando
Best Practices Cloud Platforms
130+ Free Data Sources For Data Science
- General And Academic
- Content Marketing
- Crime
- Drugs
- Education
- Entertainment
- Environmental And Weather Data
- Financial And Economic Data
- Government And World
- Health
- Human Rights
- Labor And Employment Data
- Politics
- Retail
- Social
- Travel And Transportation
- Various Portals
- Source Articles and Blog Posts
- Free Data Sources Data Science
1001 Interview Questions
Recommended Books, Courses, and Podcasts
How To Contribute
If you have some cool links or topics for the cookbook, please become a contributor.
Simply pull the repo, add your ideas and create a pull request. You can also open an issue and put your thoughts there.
Please use the "Issues" function for comments.
Important Links
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