Step 1: import csv into mysql Download data from kaggle: https://www.kaggle.com/barelydedicated/bank-customer-churn-modeling create database in MySQL Create table within database Import csv into table. Replace what is between < >. If you get the following error “The MySQL server is running…
Category: Jupyter Notebook
How to Extract Title and Text from Scraped Article
Say you have successfully extracted the full HTML of multiple articles using a web crawler and stored it in a database. You can easily extract the title and text from this article. In this tutorial, the data is being stored…
Extract Provided Keywords and Their Synonyms from News Articles
In Jupyter Notebook: Open Anaconda Prompt and conda activate your environment. Otherwise, create a new environment and activate it. Run jupyter notebook. Import statements: Connect to MongoDB database collection. Fill in any info between <>. In this example, the database…
Using Stanford OpenIE with Ubuntu on VirtualBox
Use Vagrant and VirtualBox to set up a local Ubuntu installation. Run the VirtualBox, steps here. In the command line, cd into /vagrant_data: Install Java 8: Download Stanford CoreNLP here and extract it. cd into the stanford-corenlp directory and run…
How to Reproduce Your Conda Environment
You may have created a conda environment with specific versions of dependencies needed to run your script. What happens when you need to run this script on another computer? You can simply export the environment in a .yml file and…
Performing Named Entity Recognition
Named Entity Recognition involves identifying portions of text representing labels such as geographical location, geopolitical entity, persons, etc. In this tutorial, we will use deep learning to identify various entities in Medium articles and present them in useful way. In…
Creating a Text Summarizer Using Natural Language Processing
There are several methods of generating summaries for text. In this tutorial, I will be covering an extractive method in which the top 2 most important sentences in an article serve as the summary. This method uses GloVe, cosine similarity…
Creating a Text Summarizer Using the Heap Queue Algorithm
Text summarization is useful for highlighting crucial information for business such as buying signals. There are some simple methods of summarizing text, although less effective than using deep learning. In this tutorial we will be using the Heap queue algorithm…
Predicting Art Genre
I’ve opened a kaggle account and used the Best Artworks of All Time dataset to train models to make predictions on art genre based on century and nationality. Kaggle allows me to load the Jupyter Notebook web app and write…