Why McKinsey Analytics + Ken Benoit Talk
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Text Mining Hackathon has started! Yesterday at 5pm UTC we had a pleasure to kick-off Why R? 2020 conference and the Text Mining Hackathon with Julia Silge keynote talk Data visualization for machine learning practitioners. The hackathon lasts for 24hours so you still have a chance to join! Especially since there are 4 various challenges and you can pick one if you do not have enought time for all 4. The deadline for solutions is 2020-09-24 5:30PM UTC!
Today we have 2 great talks at the Hackathon.
- 2020-09-24 1:00pm UTC Kenneth Benoit Why you should stop using other text mining packages and embrace quanteda - stream
- 2020-09-24 5:30pm UTC Why McKinsey Analytics? And how we use technology, data and global capabilities to serve our clients? - stream
Find out descriptions below
The text analysis package quanteda is now a mature package with a large user base, and interwoven with a growing family of related packages for machine learning, text conversion, part-of-speech tagging and dependency parsing, and sentiment analysis. I outline the reasons why you should be using it and what it can do for your natural language processing and text analysis needs.
McKinsey & Company perform many engagements with strong analytics components. Our data scientists and architects, together with our machine learning and data engineers, complement our strategic and operational consulting and provide our clients with advanced and robust data-driven solutions. In this introduction to McKinsey Analytics, you will learn how our data professionals work and leverage technology to create the impact across the globe. As the part of our technology stack, you will be introduced to Kedro. Kedro is an open-source framework that helps you apply software engineering best-practice to data and machine-learning pipelines. It shines when multiple data scientists are collaborating on a project and need a consistent and standard way of working together.
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