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tabula-py

Simple wrapper of tabula-java: extract table from PDF into pandas DataFrame

talks

Personal talks

talks-1

A collection of talks presented at Python Frederick

technical-ebooks

PDFs for programming tutorials.

technical-interview-prep

These are coding solutions for problems I study while preparing for technical interviews at tech companies

tensorflow-examples

TensorFlow Tutorial and Examples for Beginners with Latest APIs

tesseract

Tesseract Open Source OCR Engine (main repository)

text-analytics-with-python

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

text-mining-ba

Assignments and slides for text-mining BA

text-scraping-document-clustering-topic-modeling

The objective of this project is to scrape a corpus of news articles from a set of web pages, pre-process the corpus, and then to apply unsupervised clustering algorithms to explore and summarise the contents of the corpus. Part 1. Text Data Scraping This part of the project should be implemented as a Python script 1. Identify the URLs for all news articles listed on the website: http://mlg.ucd.ie/modules/COMP41680/news/index.html 2. Retrieve all web pages corresponding to these article URLs. 3. From the web pages, extract the main body text containing the content of each news article. Save the body of each article as plain text. Part 2. Corpus Exploration Tasks to be completed in your IPython notebook: 1. Load the text corpus generated in Part 1. Apply any appropriate pre-processing steps and construct a document-term matrix representation of the corpus. 2. Summarise the overall corpus by identifying the most characteristic terms and phrases in the corpus. 3. Apply two alternative clustering algorithms of your choice to the document-term matrix to produce clusters of related documents. This might require applying each algorithm several times with different parameter values. 4. For each clustering generated in Step 3, summarise the contents of the clusters. Based on your summary, suggest a topic/theme for each cluster.

textract

extract text from any document. no muss. no fuss.

thesemicolon

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

threading-queue

Code for Threading + Queue videos

tidy-text-mining

Manuscript of the book "Tidy Text Mining with R" by Julia Silge and David Robinson

tidyextractors

A collection of tools for extracting tidy data.

titanic_challenge

Titanic Challenge Repo

tkinter-by-example

Learn Tkinter By Example - a free book

tkinterpractice

Practicing with Tkinter for Graphical User Interfaces in Python

training-ai

trumpscript

Make Python great again

tutorial-r-web-data

Introduction to getting data from the web with R

tutorials

This contains the code I used in my R and Python scraping tutorials, located here:

tutorials-1

Code for all my tutorials

twittervarientspellings

Code for searching Twitter for variant spellings.

unholy

a ruby-to-pyc compiler

unlock-excel-vba-excel-macros---udemy-course-by-leila-gharani

urban-data-science

Course materials, Jupyter notebooks, tutorials, guides, and demos for a Python-based urban data science course.

username_tools

vba-web

VBA-Web: Connect VBA, Excel, Access, and Office for Windows and Mac to web services and the web

vba-xml

XML conversion and parsing for VBA