Kafka-ML: Connecting the data stream with ML/AI frameworks

Evaluation of Stream Processing Frameworks

(2020) Giselle van Dongen et al.   IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS

Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey

(2019) Giang Nguyen et al.   ARTIFICIAL INTELLIGENCE REVIEW

Action recognition using optimized deep autoencoder and CNN for surveillance data streams of non-stationary environments

(2019) Amin Ullah et al.   Future Generation Computer Systems-The International Journal of eScience

Tera-scale coordinate descent on GPUs

(2018) Thomas Parnell et al.   Future Generation Computer Systems-The International Journal of eScience

Towards a proper service placement in combined Fog-to-Cloud (F2C) architectures

(2018) V.B. Souza et al.   Future Generation Computer Systems-The International Journal of eScience

Distributed data stream processing and edge computing: A survey on resource elasticity and future directions

(2018) Marcos Dias de Assunção et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

Why Jupyter is data scientists’ computational notebook of choice

(2018) Jeffrey M. Perkel   NATURE

Data Lifecycle Challenges in Production Machine Learning

(2018) Neoklis Polyzotis et al.   SIGMOD RECORD

Apache Spark

(2016) Matei Zaharia et al.   COMMUNICATIONS OF THE ACM

State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing

(2016) Manuel Díaz et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

Fog and IoT: An Overview of Research Opportunities

(2016) Mung Chiang et al.   IEEE Internet of Things Journal

Deep learning

(2015) Yann LeCun et al.   NATURE