In this presentation and linked notebooks we learn the basics of creating a machine learning classifier from scratch using language classification as a running example. We start by implementing the naive intuition that letter frequency could provide a model for language classification, and then we will implement the n-gram paper from Cavnar and Trenkle. In corresponding notebook we will create a Spark ML Transformer from the n-gram model that can be used to classify text in a Dataset or Dataframe

1. Exploring Language Classification
With Apache Spark and the Spark Notebook
A practical introduction to interactive Data Engineering
Gerard Maas

2. Gerard Maas
Lead Engineer @ Kensu
Computer Engineer
Scala Programmer
Early Spark Adopter
Spark Notebook Dev
Cassandra MVP (2015, 2016)
Stack Overflow Top Contributor
(Spark, Spark Streaming, Scala)
Wannabe IoT Hacker
Arduino Enthusiast
@maasg
https://github.com/maasg
https://www.linkedin.com/
in/gerardmaas/
https://stackoverflow.com
/users/764040/maasg

3. DATA SCIENCE GOVERNANCE
Adalog helps enterprises to ensure that data pipelines continually deliver
their value by combining the contextual information when the pipeline was
created with the evolving environment where the pipelines execute.
CONNECT - COLLECT - LEARN

5. Language Classification

6. Language Classification
Some inspiration...

7. What’s is a language? How is it composed?

8. Letter Frequency
Could we characterize a language by calculating the relative frequency of letters in some
text ?
Spanish vs English letter frequency

9. n-grams
"cavnar and trenkle"
bi-grams: ca,av,vn,na,ar,r_,_a,an,nd,d_,_t,tr,re,en,nk,kl,le,e_
tri-grams: cav,avn,vna,nar,ar_,r_a,_an,and,nd_,d_t,_tr,tre,ren,enk,nkl,kle,le_
quad-grams: cavn,...
http://odur.let.rug.nl/~vannoord/TextCat/textcat.pdf
Could we characterize a language by calculating the relative frequency of sequence of
letters in some text ?

10. Tech

12. Spark APIs
RDD -> Resilient Distributed Datasets
- Lazy, functional-oriented, low level API
- Basis for execution of all high-level libraries
Dataframes
- Column-oriented, SQL-inspired DSL
- Many optimizations under the hood (Catalyst, Tungsten)
Dataset
- Best of both worlds (except …)

13. Spark Notebook
A dynamic and visual web-based notebook for Spark
with Scala

14. Spark Notebook - Open Source Roadmap
2017
GIT Kerberos
Project
Generator
Q1 Q2 Q3
Announcements: blog.kensu.io

15. Notebooks
Notebooks for this presentation are located at:
https://github.com/maasg/spark-notebooks
- have fun!

16. https://github.com/maasg/spark-notebooks/languageclassification/language-detection-letter-freq.snb
Implements the idea of using a letter frequency model to classify the language in a doc.
Uses the dataset found in https://github.com/maasg/spark-notebooks/languageclassification/data/
It produces a training set of sampled strings that will be used also for the n-gram classifier
(Note: this notebook is missing a function that’s left as an exercise to the reader. The folder
/solutions contains the full working version.)
Notebook 1 : Naive Language Classification

17. Notebook 2 : n-gram Language Classification
https://github.com/maasg/spark-notebooks/languageclassification/n-gram-language-classification.snb
Implements the n-gram algorithm described in the paper.
Uses the dataset found in https://github.com/maasg/spark-notebooks/languageclassification/data/
Uses the resulting classifier to implement a custom Spark ML Transformer that can be easily used to classify
new texts. Transformers can be combined into Spark ML Pipelines of arbitrary complexity.
(Note: this notebook is missing a function that’s left as an exercise to the reader. The folder
/solutions contains the full working version.)