2vec or not2vec

awesome 2vec
awesome embedding models
something2vec

Swift Mindmap

Swift Language Guide

Swift Language Reference

awesome-swift1

awesome-swift2

swift lib hunt

Immutablejs

Immutablejs

Curl

Curl

Big Data Ecosystem

Big Data Ecosystem Table
Hadoop Ecosystem
Hadoop Illuminated
Big Data
Hortonworks Big Data Projects
Big Data for Science

Minio

Minio

Ways to Query S3

S3->Redshift->Quicksight
S3->Redshift Spectrum
S3->EMR for ad hoc queries
S3->Presto
S3->Athena
S3->S3API
S3->Drill
S3->Impala
S3->Hive
...

SQLStream

SQLStream

PipelineDB

PipelineDB

SWRL

• SWRL
• OWL2 & SWRL
• A Proposal for SWRL Extension Towards First Order Logic

Ontology-Based Data Access

• Ontology-Based Data Access
• The Bag Semantics of Ontology-Based Data Access
• Ontology-Based Data Access: A Study Through Disjunctive Datalog, CSP, MMSNP
• The Combined Approach to Ontology-Based Data Access
• Introduction to Ontology-Based Data Access

Jester Recommendation

Jester

Qubole

Qubole

Alteryx

Alteryx

Datameer

Datameer

Dataiku

Dataiku

DBSCAN

• Density Level Set Estimation on Manifolds with DBSCAN
• Random Forest DBSCAN for USPTO Inventor Name Disambiguation
• Design and Optimization of DBSCAN Algorithm Based on CUDA
• Analysis and Study of Incremental DBSCAN Clustering Algorithms
• Performance Comparison of Incremental K-Means and Incremental DBSCAN Algorithms
• A Density Algorithm for Discovering Clusters in Large Spatial Databases with Noise
• Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and its Applications
• DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN

RecommenderLab

RecommenderLab

Instantaneously Trained Neural Networks

Instantaneously Trained Neural Networks

Types of Recommendation Engines

Neighborhood-Based Recommendations:

• User-Based Collaborative Filtering
• Item-Based Collaborative Filtering

Personalized Recommendations:

• Context-Aware
• Context-Based

Model-Based Recommendations:

• ML-Based
• SVM/KNN Classification
• Matrix Factorization
• Singular Value Decomposition
• Alternating Least Squares
• Hybrid (Methods: Weighted, Mixed, Switching, Cascade, Feature Combination, Feature Augmentation, Meta-Level, etc)

ML Techniques Applied to Recommendations:

• Euclidean Distance
• Cosine Similarity
• Jaccard Similarity
• Pearson Correlation Coefficient
• Matrix Factorization
• Alternating Least Squares
• Singular Value Decomposition
• Linear Regression
• Classification Models
• K-Means Clustering
• Principal Component Analysis
• Term Frequency
• Term Frequency-Inverse Document Frequency

Evaluations:

• Root-Mean-Square Error
• Mean Absolute Error
• Precision and Recall

KXDate

KXDate

Spring Big Data

Spring Cloud
Spring Cloud DataFlow
Spring Data
Spring Kafka
Spring StateMachine

KotlinTest

KotlinTest

Open Market Data Providers

Quandl
Yahoo Finance
Google Finance
Thomson Reuters Open APIs
SimFin
Alpha Vantage
CurrencyDataFeed
1Forge
Intradata
Knoema
OlsenData
OpenExhangeRates
Financial Content
Oanda
XE
Xignite
CurrencyLayer
EODData
European Central Bank Feeds
ICE Consolidated
IEX
Polygon.io
Intrinio
DxFeed
Funds Library

Apache Calcite

Apache Calcite