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UID:pretalx-fosscomm-2020-LFYXLA@pretalx.fosscomm.gr
DTSTART;TZID=EET:20201122T120000
DTEND;TZID=EET:20201122T123000
DESCRIPTION:Data Analytics (DA) and Machine Learning (ML) in the Big data e
 ra depend heavily on handling huge volumes of data efficiently and in a ge
 neric way\, exploiting standardized protocols for interface and storage co
 mpatibility. However\, implementation-agnostic functionality is necessary 
 to ensure application decoupling and easy maintenance of the DA/ML codebas
 e. In many cases\, SQL aggregations and statistics extensions can provide 
 a similar abstraction layer\, but this usually comes at the cost of constr
 ucting very lengthy and complex queries for functionality that can be impl
 emented in just few lines of code e.g. in Python\, or cannot be implemente
 d at all if it requires advanced statistics\, machine learning algorithms 
 or hardware acceleration. “Sequoia” is a starting codebase for such a 
 generic abstraction layer between DA/ML and data management\, providing an
  SQL-like scripting language with rich and “dense” functionality with 
 minimal implementation details exposed to the application level. It provid
 es a full compiler/interpreter developed in pure Python with lex/yacc func
 tionality\, implementing DA/ML “primitives” like unified data source i
 mport and in-memory database\, automated data pre-processing (e.g. missing
  values removal\, error checking\, noise removal\, trend removal\, normali
 zation\, rescaling)\, data resampling\, advanced statistics\, n-order regr
 ession\, etc. More advanced primitives can provide adaptive signal process
 ing for time series\, including Wiener filtering\, Kalman filtering\, RLS/
 LMS filtering\, etc. Furthermore\, it can be easily extended to applicatio
 n-specific functionality\, e.g. implementing 2-D convolutions via TensorFl
 ow with only one line of the custom Sequoia language. The library is curre
 ntly under development and provides interpreter functionality\, while in t
 he next versions it will also provide pre-compiled intermediate forms in t
 he sense of Just-In-Time compilation for much faster execution in the Sequ
 oia engine. It is also a very useful educational tool for academic courses
  in compiler theory and advanced programming in Python.
DTSTAMP:20260512T060612Z
LOCATION:Αίθουσα 1
SUMMARY:Sequoia: Building a compiler/interpreter for an SQL-like data analy
 tics language using Python - Harris Georgiou
URL:https://pretalx.fosscomm.gr/fosscomm-2020/talk/LFYXLA/
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