grakn
PythonDataScienceHandbook
grakn | PythonDataScienceHandbook | |
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11 | 98 | |
3,671 | 41,540 | |
0.4% | - | |
9.3 | 0.6 | |
7 days ago | 10 days ago | |
Java | Jupyter Notebook | |
Mozilla Public License 2.0 | MIT License |
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grakn
- Datomic Is Now Free
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Best Websites For Coders
TypeDB : A Strongly-typed Database
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Fluree DB - A datomic like database that I just discovered
How does it compare to, say grakn (renamed https://vaticle.com/, I think?), or draph (https://dgraph.io/), or Ontotext's GraphDB (https://www.ontotext.com/products/graphdb/), or Datomic?
- Typedb
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Firebase is Dead: What is the Perfect Database in 2022?
Edge database looks pretty freakin awesome. It basically seems to re-write SQL and Graph databases together to create some new-ish programming language. It takes care of all the problems GraphQL has, and seems to be built separately but on top of postgres. It is really something unique, beautiful, and powerful. They don't have a security layer yet or a cloud hosting environment, but both are in the works. However, postgres still suffers from the scalable problems we all know. If you like unique fetching and strong typing, also check out TypeDB. It doesn't make its own list number because there is not cloud version, middleware, etc. However, worth checking out.
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Ask HN: Why are relational DBs are the standard instead of graph-based DBs?
If you find yourself limited by triplestores, there's also a new growing area of development in knowledge engines, which allow edges-of-edges, entailed relations, hypergraph relations, and more of the power you'd get from full logic programming. TypeDB (recently renamed from Grakn) is an example of that type of database.
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How Roche Discovered Novel Potential Gene Targets with TypeDB
In the story to follow, David presents how his team at Roche was able to identify potential novel targets that were not identified by Open Targets as highly ranked. This was made possible with TypeDB, which his team used to store the relevant data and then find underlying biological evidence for those new targets.
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Why are the downloaded zip files not in scope?
{ stdenv, lib, openjdk,typedbHome ? "~/.typedb_home", fetchzip}: let typedbVersion = "2.1.1"; typedbDirLinux = "typedb-all-linux-${typedbVersion}"; typedbDirMac = "typedb-all-mac-${typedbVersion}"; typedbDirWindows = "typedb-all-windows-${typedbVersion}"; typedbDir = if stdenv.hostPlatform.isWindows then typedbDirWindows else if stdenv.isDarwin then typedbDirMac else typedbDirLinux; linuxSrc = builtins.fetchTarball { url = "https://github.com/vaticle/typedb/releases/download/2.1.1/typedb-all-linux-2.1.1.tar.gz"; sha256 = "15nwm2dr68p67c2xcqigs66gd679j1zr72gqv7qxgvflwyvyz8fb"; }; windowsSrc = fetchzip { url = "https://github.com/vaticle/typedb/releases/download/2.1.1/typedb-all-windows-2.1.1.zip"; sha256 = "0vd66gfshkg697z07nhy957mwqzlli4r4pmn67hx58n9mkg024kq"; }; macSrc = fetchzip { url = "https://github.com/vaticle/typedb/releases/download/2.1.1/typedb-all-mac-2.1.1.zip"; sha256 = "16hlfy6kh2rnvcralz206q13mghb0rv8wazpg6q3h324p5rdys54"; }; srcFolder = if stdenv.hostPlatform.isWindows then windowsSrc else if stdenv.isDarwin then macSrc else linuxSrc ; javaPatch = '' 20c20 < JAVA_BIN=java --- > JAVA_BIN=${openjdk}/bin/java ''; in stdenv.mkDerivation rec { pname = "typedb"; version = typedbVersion; src = srcFolder; phases = [ "installPhase" ]; buildDepends = [ openjdk ]; installPhase = '' echo "here" # added for debugging ls -lah # " echo "--" # " #patch before install echo "${javaPatch}" > typedb_java.patch patch ./${typedbDir}/typedb typedb_java.patch mkdir $out cp -r ./${typedbDir} $out # add a wrapper script to $out that will move typedb to $typedb # this is necessary because typedb needs a writable environment echo " # on the first start copy everything to typedbHome if [ ! -f ${typedbHome}/typedb ]; then mkdir -p ${typedbHome}; cp -r $out/${typedbDir}/* ${typedbHome}; # correct permissions so that typedb and the user can write there chmod -R u+rw ${typedbHome} chmod u+x ${typedbHome}/typedb fi; ${typedbHome}/typedb \$@; " > $out/typedb chmod +x $out/typedb ''; doCheck = true; meta = with lib; { description = "TypeDB is a distributed knowledge graph: a logical database to organise large and complex networks of data as one body of knowledge."; longDescription = '' TypeDB is a distributed knowledge graph: a logical database to organise large and complex networks of data as one body of knowledge. TypeDB provides the knowledge engineering tools for developers to easily leverage the power of Knowledge Representation and Automated Reasoning when building complex systems. Ultimately, TypeDB serves as the knowledge-base foundation for intelligent systems. ''; homepage = "https://www.grakn.ai/"; license = licenses.gpl3Plus; platforms = platforms.all; maintainers = [ maintainers.haskie ]; }; }
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Best Websites Every Programmer Should Visit
grakn.ai : The Database for AI
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Need Graph Db Recommendations Lightweight Neo4j
Give the open-source Grakn a look as well (full transparency: I work there), it is an abstraction over a built in-house hypergraph storage engine and persisted layer using RocksDB. It's a logical database with a reasoning engine at the database level. https://github.com/graknlabs/grakn
PythonDataScienceHandbook
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About Data analyst, data scientist and data engineer, resources and experiences
Python Data Science Handbook
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Where to learn data science with python??
Python Data Science Handbook — learn to use Python libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools to effectively store, manipulate, and gain insight from data
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Book Recommendations
I don't know what tools you will be using but if you will be using Python you can start with Python Data Science Handbook by Jake VanderPlas and Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting DataData Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data which gives a very good outlook on the data science and big data frame work. PS: Jake's book is also available as jupyter notebooks so you can read and run the code at the same time.
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Other programing options?
Python Data Science Handbook by Jake VanderPlas (https://jakevdp.github.io/PythonDataScienceHandbook/)
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Pathways out of GIS?
Otherwise you can work through courses on Datacamp, Coursera, Udemy, etc, or check out this book for a more general non-spatial perspective.
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Mastering Data Science: Top 10 GitHub Repos You Need to Know
7. Data Science Handbook Are you looking for a comprehensive guide to data science with Python? Look no further than the Data Science Handbook by Jake VanderPlas. This repository contains the entire book, which introduces essential tools and techniques used in data science, including IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It’s a fantastic resource for anyone looking to deepen their understanding of data science concepts and best practices.
- Help a lady out (career advice(
- Resources for Current DE Interested in Learning Data Science
- Good book or course to learn Python for someone who is fluent in R?
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Python equivalent to R's ecosystem of open source educational materials
I can recommend https://jakevdp.github.io/PythonDataScienceHandbook/
What are some alternatives?
datalevin - A simple, fast and versatile Datalog database
django-livereload-server - Livereload functionality integrated with your Django development environment.
asami - A graph store for Clojure and ClojureScript
Exercism - Scala Exercises - Crowd-sourced code mentorship. Practice having thoughtful conversations about code.
topic-db - TopicDB is a topic maps-based semantic graph store (using SQLite for persistence)
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
datahike - A durable Datalog implementation adaptable for distribution.
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
OSQuery - SQL powered operating system instrumentation, monitoring, and analytics.
gremlin-scala - Scala wrapper for Apache TinkerPop 3 Graph DSL
devdocs - API Documentation Browser