>>> from sklearn.feature_extraction.text import TfidfTransformer
>>> transformer = TfidfTransformer(smooth_idf=False)
>>> transformer
TfidfTransformer(norm=...'l2', smooth_idf=False, sublinear_tf=False,
                 use_idf=True)

2018-06-20

ML►app►nlp

nltk

keras

doc: https://keras.io/preprocessing/text/

example_code:

https://machinelearningmastery.com/prepare-text-data-deep-learning-keras/

tensorflow

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/learn/python/learn/preprocessing/text.py

pytorch

2018-06-20

ML►app►vision

##

autoencoder是自己预测自己

word2vec是针对时序

markov autoencoder呢？

2018-06-20

ML►app►vision►-tools

web camera using Java

I have tried number of ways to do this, from a long time.

JMF - Now it is dead
FMJ - Now it is dead too
VLCJ - too much because I am not creating a music/video player and it expect VLC to be installed
Xuggler - too much and hard work
JMyron - didn’t work
JavaFX - I thought it could do it, but seems like it can’t

JavaCV http://docs.opencv.org/2.4/doc/tutorials/introduction/desktop_java/java_dev_intro.html

https://github.com/sarxos/webcam-capture

##

2018-06-20

ML►app►vision►app►OCR

Document/Layout Analysis for OCR

Before the “character” recognition will take place, the logical structure of the document has to be be analyzed and defined. For example:

Where are text blocks, paragraphs, lines?
Is there a table that should be reconstructed?
Are there any “images” on the page(s)?
Are there any barcodes to read?

https://abbyy.technology/en:features:ocr:document_analysis

2018-06-20

ML►app►vision►app►OCR

document layout ocr

全局layout–

tesera oCR出样式吗？
上下级，平行关系。

法律条款的额结构分析。

OCR结构 – 识别内容，，相互加强。multi-task 学习。。

collection –

2018-06-20

ML►app►vision►app►OCR►Tesseract-OCR