From 9b8f66da58cbc6d78b875d372e7d2e788629ec4e Mon Sep 17 00:00:00 2001 From: ErdemOzgen Date: Mon, 4 Dec 2023 14:49:38 +0300 Subject: [PATCH] Add TODOs and update content --- README.md | 10 ++++++++++ content/AI&DATA/Generative AI By GOOGLE.md | 5 +++-- content/Devops&DevSecOps/Index.md | 0 .../{KEGM DevSecOps.md => Testing AzureDevOps.md} | 0 content/SoftwareEnginnering/Index.md | 2 ++ content/SoftwareEnginnering/test.md | 11 ----------- 6 files changed, 15 insertions(+), 13 deletions(-) create mode 100644 content/Devops&DevSecOps/Index.md rename content/Devops&DevSecOps/{KEGM DevSecOps.md => Testing AzureDevOps.md} (100%) create mode 100644 content/SoftwareEnginnering/Index.md delete mode 100644 content/SoftwareEnginnering/test.md diff --git a/README.md b/README.md index 4b4731c9b..d14db6256 100644 --- a/README.md +++ b/README.md @@ -18,3 +18,13 @@ Quartz v4 features a from-the-ground rewrite focusing on end-user extensibility

+ + +# TODOS + +```bash +npm i +#npx quartz create +# npx quartz build --serve # local serve +npx quartz sync +``` \ No newline at end of file diff --git a/content/AI&DATA/Generative AI By GOOGLE.md b/content/AI&DATA/Generative AI By GOOGLE.md index 92f4302b2..6313b6f58 100644 --- a/content/AI&DATA/Generative AI By GOOGLE.md +++ b/content/AI&DATA/Generative AI By GOOGLE.md @@ -1,6 +1,7 @@ ## # What are the 4 Vs of Big Data?  There are generally four characteristics that must be part of a dataset to qualify it as big data—volume, velocity, variety and veracity [link](https://bernardmarr.com/what-are-the-4-vs-of-big-data/#:~:text=There%20are%20generally%20four%20characteristics,%2C%20velocity%2C%20variety%20and%20veracity.) +#etl ### What is ETL @@ -10,8 +11,8 @@ ETL provides the foundation for data analytics and machine learning workstreams. - Cleanse the data to improve data quality and establish consistency - Load data into a target database - -### Apache Beam +#apachebeam +### Apache Beam Apache Beam is an open-source, unified programming model and set of tools for building batch and streaming data processing pipelines. It provides a way to express data processing pipelines that can run on various distributed processing backends, such as Apache Spark, Apache Flink, Google Cloud Dataflow, and others. Apache Beam offers a high-level API that abstracts away the complexities of distributed data processing and allows developers to write pipeline code in a language-agnostic manner. The key concept in Apache Beam is the data processing pipeline, which consists of a series of transforms that are applied to input data to produce an output. A transform represents a specific operation on the data, such as filtering, mapping, aggregating, or joining. Apache Beam provides a rich set of built-in transforms, as well as the ability to create custom transforms to suit specific processing needs. diff --git a/content/Devops&DevSecOps/Index.md b/content/Devops&DevSecOps/Index.md new file mode 100644 index 000000000..e69de29bb diff --git a/content/Devops&DevSecOps/KEGM DevSecOps.md b/content/Devops&DevSecOps/Testing AzureDevOps.md similarity index 100% rename from content/Devops&DevSecOps/KEGM DevSecOps.md rename to content/Devops&DevSecOps/Testing AzureDevOps.md diff --git a/content/SoftwareEnginnering/Index.md b/content/SoftwareEnginnering/Index.md new file mode 100644 index 000000000..103426492 --- /dev/null +++ b/content/SoftwareEnginnering/Index.md @@ -0,0 +1,2 @@ +# Software Engineering + diff --git a/content/SoftwareEnginnering/test.md b/content/SoftwareEnginnering/test.md deleted file mode 100644 index 68c56b6ec..000000000 --- a/content/SoftwareEnginnering/test.md +++ /dev/null @@ -1,11 +0,0 @@ -# Software Enginnering -adsmsadsa -d -asd -as -d -as -da -sd -as -d