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Category: Machine Learning

  • AI
  • AI Testing
  • ChatGPT
  • Hugging Face
  • Machine Learning
  • python

Baseline Model Comparison for Performance Evaluation

Machine learning models evolve. As a tester, how do we know the newer version of the model is better? How do we know that the model did not get worse in other areas? The most intuitive approach would be to design a ‘good’ labelled dataset and then calculate the evaluation score like the F1 score for the model under test. […]

July 24, 2023November 22, 2023
  • AI
  • Machine Learning
  • testing

Testers, practice testing a machine learning algorithm!

Testers, you now have an app you can use to practice testing a machine learning algorithm. We have written and hosted a simple sentence classifier for testers to practice testing a machine learning algorithm. Play with it and let us know what fun bugs you discover. Hint: Testing this app is fun because there are several bugs that are not […]

November 29, 2020December 3, 2020
  • Extracting data
  • Machine Learning
  • Natural Language Generation
  • Uncategorized

Identify tech words from a text

As part of the pairing project activity at Qxf2 – pick a project that can produce a meaningful output in 5 hours and work on it collaborating with your team mates, I picked this project to identify the tech keywords from a text using NLTK module. This post covers the steps I followed to find the tech related words in […]

August 21, 2019
  • automation
  • Data scraping
  • Extracting data
  • Machine Learning

Scraping websites using Octoparse (no programming!)

Did you know you can scrape data from webpages without writing a single line of code? In this post, we will talk about a tool called Octoparse. We used Octoparse to scrape data from a list of URLs, without any coding at all. Data is valuable and it’s not always easy to get the correct data from the web sources […]

November 9, 2017April 2, 2018
  • Data Versioning
  • Machine Learning
  • quilt

Organize and edit your test data with Quilt

We recently stumbled upon Quilt, a data package manager that wants to fill the role of ‘Github for data’. We have enjoyed using it so far. We think it can be useful for testers to manage their test data using Quilt. In this post, we will take an example dataset and show you step by step guide on how to […]

October 30, 2017April 2, 2018
  • Data Versioning
  • Extracting data
  • Machine Learning
  • python
  • quilt

Quilt – a Data Package Manager

We have been testing data-rich applications for a long time. And like any experienced tester, we realize how difficult it is to create, maintain and update data every time the data model changes. So we were excited to come across Quilt, a data package manager, via Hacker News. We were thrilled that it integrated well with our favorite programming language […]

October 9, 2017April 2, 2018
  • Data visualization
  • Jupyter Notebooks
  • Machine Learning
  • python

Getting started with Jupyter Notebooks

This post is for those who want to get started with Jupyter Notebooks. You don’t need to know anything beyond Python to start using Jupyter notebook. In this post I will be covering below topics. What is a Jupyter Notebook and app? How to install and use Jupyter Notebook Jupyter notebook user interface Sharing Jupyter Notebooks via GitHub Gist and […]

October 9, 2017April 2, 2018
  • Data scraping
  • Extracting data
  • Machine Learning

Extracting data from PDFs using Python

When testing highly data dependent products, I find it very useful to use data published by governments. When government organizations publish data online, barring a few notable exceptions, it usually releases it as a series of PDFs. The PDF file format was not designed to hold structured data, which makes extracting data from PDFs difficult. In this post, I will […]

August 16, 2017April 2, 2018
  • Data Sources
  • Machine Learning
  • Mockaroo Dataset

Mockaroo Tutorial: Generate realistic test data

At a recent client engagement, my colleague had to create some location data for testing one of the client application. The data creation involved multiple steps like downloading some data from the net, removing some columns, transforming it as per needs using Python code. The process was a bit time-consuming. Recently when I was searching for some tools for data […]

July 17, 2017April 24, 2018
  • Data scraping
  • Machine Learning
  • Pandas
  • python

Scraping a Wikipedia table using Python

A colleague of mine tests a product that helps big brands target and engage Hispanic customers in the US. As you can imagine, they use a lot of survey data as well as openly available data to build the analytics in their product. We do test the accuracy of the underlying algorithms. But the algorithms used are only going to […]

June 12, 2017April 2, 2018

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