Pygrametl
Petl
Bubbles
Pandas
PyQuery
MrJob
Celery
AWS
Luigi
PySpark
Lxml
BeautifulSoup
Scrapy
Airflow
PyParsing
Dataset
Dask
Blaze
Riko
Retrying
school of data
10 January 2017
9 January 2017
Dark Patterns
Dark Patterns linger on the web as a tell tale signs of user deception and trickery. Often unnoticed by the user through the interface where they are purposely and intentionally made to confuse. They set on a gamut of actions which are unauthorized by the user. The darkpatterns.org provides further details on examples of deliberately confusing and deceptive user interfaces. There are also shady patterns which push boundaries for user desires but are not deliberately deceptive in practice. They may be construed as misdirections with unclear language which tend to trick a user into doing things that they would otherwise not intentionally do. Many companies are aware of such practices but slither within the boundaries of safe zones. And often signs of such deceptions linger in the use of language, the misdirections, as well as when there are too many things happening on the site. Some ads are also deliberately deceptive which use behavior targeting, follow user's web history, and search patterns.
Labels:
big data
,
contextual ads
,
data science
,
intelligent web
,
interaction design
,
interface design
,
linked data
,
machine learning
,
security
,
web design
8 January 2017
Hortonworks Toolset
- Falcon
- Atlas
- Sqoop
- Flume
- Kafka
- NFS
- WebHDFS
- Hadoop
- Hadoop MapReduce
- Hadoop HDFS
- Hadoop YARN
- Pig
- Hive
- HBase
- Accumulo
- Phoenix
- Storm
- Solr
- Spark
- Hawq
- Zepplin
- Nifi
- Ranger
- Knox
- Cloudbreak
- Zookeeper
- Oozie
- Slider
- Tez
- Metron
SMACK Stack
S : Scala and Spark (The Engine)
M : Mesos (The Hardware Scheduler)
A : Akka (The Actor Model)
C : Cassandra (The Storage)
K : Kafka (The Message Broker)
A Brief History of Smack
Smack Hands-On
Smack Made Simple
Smack Guide
why is smack stack all rage lately
Smack Slideshare
Smack Personalization
Alternatives for Stream Analytics:
GearPump
Flink
M : Mesos (The Hardware Scheduler)
A : Akka (The Actor Model)
C : Cassandra (The Storage)
K : Kafka (The Message Broker)
A Brief History of Smack
Smack Hands-On
Smack Made Simple
Smack Guide
why is smack stack all rage lately
Smack Slideshare
Smack Personalization
Alternatives for Stream Analytics:
GearPump
Flink
Labels:
akka
,
big data
,
cassandra
,
data science
,
distributed systems
,
hadoop
,
kafka
,
machine learning
,
nosql
,
reactive
,
scala
,
spark
16 December 2016
8 December 2016
Web Scraping Services
Labels:
big data
,
data science
,
distributed systems
,
intelligent web
,
metadata
,
natural language processing
,
semantic web
,
text analytics
,
webcrawler
,
webscraper
,
webservices
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