Python 3.x, and in particular Python 3.5, natively supports asynchronous programming. While asynchronous code can be harder to read than synchronous code, there are many use cases were the added complexity is worthwhile. One such examples is to execute a…
Symbiosen mellem mennesker og AI vil kunne transformere mennesket til en rationel organisme (jvf. Daniel Kahneman som har påvist at mennesket for sig selv ikke er en rationel organisme). Hvordan det? Vores minutiøse adfærd bliver i stigende grad sporet i…
Here is an analytical query that you (and I) will often need to do if you work in e-commerce, marketing or similar domain. It answers the question, within each group of items (e.g. partitioned by territory, age groups or something…
Wikipedia contains a wealth of knowledge. While some of that knowledge consists of natural language descriptions, a rich share of information on Wikipedia is encoded in machine-readable format, such as infoboxes and other specially formatted parts. An infobox is rendered…
Whenever two things have a directional relationship to each other, then you can compute the pagerank of those things. For example, you can observe a directional relationships between web pages that link to each other, scientists that cite each other,…
I like to code in Python. I also like the concept of asynchronous workers to build loosely coupled applications. Luckily, RabbitMQ and Celery can help me do exactly that. This post is based on a very nice YouTube video by…
Scrapy is an excellent Python library for web scraping. For example, you could create an API with data that is populated via web scraping. This article covers some basic scrapy features, such as the shell and selectors. Install scrapy in…
Pandas and SQLAlchemy offer powerful conversions between CSV files and tables in databases. Here is a small example: import pandas as pd from sqlalchemy import create_engine df = pd.read_csv(‘mydata.csv’) engine = create_engine(”) df.to_sql(‘mytable’, engine) Read more: pandas.DataFrame.to_sql sqlalchemy engines
Given an AWS credentials file that looks like this: [default] aws_access_key_id = DEFAULT aws_secret_access_key = SECRET1 [dev] aws_access_key_id = DEV aws_secret_access_key = SECRET2 [prod] aws_access_key_id = PROD aws_secret_access_key = SECRET3 You can use any profile, say dev, like this in…
You may ask yourself, if I’m a machine learning person then what kind am I? See for yourself in Jason Eisner’s Three Cultures of Machine Learning.