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Thu, 16 Jun, 17:00

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AltitudeX LDN

RebekahYates

started this topic

Accounting for inflation in price elasticity modelling

I’m wondering if anyone has done any research into/has had any success in accounting for inflation in their price elasticity modelling? Give...

ChrisBillingham

started this topic

Whats the most "fun" thing you've done with Data Science?

We often talk about the Data Science projects we do purely from a business perspective. Predicting customer behaviour, forecasting demand an...

FranBaker

started this topic

How can we use ai for good?

Hi everyone, We often hear the phrase of AI for good but I would be interested to know what examples everyone has seen and what ideas you ha...

Recent activity

FazilCommunity Member

K-means clustering algorithm from scratchNew

I've implemented vanilla k-means clustering algorithm from scratch :)https://github.com/Fazil-Math/k-means_clustering_from_scratch/blob/main/KMeans%20Clustering%20Algorithm%20From%20Scratch%20(3d%20version).ipynb

9 hours ago

laraFrequent Visitor

Communication and Visualization

Presenting technical concepts to different audiences

Many times, at the end of some piece of analysis or meeting a milestone in a project, I found myself wondering how to best present the results so that others see what I see, i.e., why I think my results are interesting and helpful to others.I’m keen to know if people have other tricks/secrets to make a presentation interesting/engaging/useful/helpful. I’ll share below my current approach for building a presentation: Understand my primary audience. Not everyone in my audience may be relevant or may be interested to take any actions on the back of my presentation so I’ll try to narrow it down to a group of people and I’ll focus to get my message across to them specifically. This doesn’t mean I ignore everyone else, I’ll try to make the presentation as inclusive as possible but without spending too much time explaining concepts that are quite common knowledge to my primary audience. Plan your presentation: how to build the story + how to present the story depending on the audience (heav

1 day ago

laraFrequent Visitor

Communication and Visualization

Choosing suitable plots for presenting results

In my first year as a PhD student, I made the massive mistake to choose the wrong type of plot to present some results to my supervisor. Obviously, that constructive feedback is stuck into my mind and I’ll never forget it now:Having great results is not enough, I also need to choose the right plot to present them. In the meantime, I found this chart that I wish I had back then. I think it helps quite a lot when deciding which plot to use depending on your data.Have you ever chosen the wrong type of plot to present your results? 😅

1 day ago

LizActive Contributor

Free Intro to Data Science book!New

A pre-release manuscript is available, ‘Data Science in Context: Foundations, Challenges, Opportunities. Could be a good resource to start learning! https://datascienceincontext.com/manuscript/

1 day ago

BenLawsonActive Contributor

Data Science in Practice

How do you add vertical gridlines between columns in the formattable R package?

I’m trying to make a copy of a visualisation of a table from Excel in R so that it can be automated as the original version is very labour intensive. From a google it seems formattable is the best package to achieve this, but I can’t find any documentation for adding lines between columns. Does anyone have experience with this package, and know how to do that?

2 days ago

Rohit2909Community Member

Questions and ideas

AI in decision Making

Hi,I wish to launch services for class 12th passing out students.i see many students are confused or unsure which stream they should follow after 12th class. They don’t what exact skill set they have and what they require to enroll into the subject of choice.Can anyone guide me how to kich start in this direction? What all is required out of “Big Data” to make it tailor made?Respect and Regards Rohit Bhatnagar

2 days ago

AndyLauCommunity Member

Data Science in Practice

When to make use of Open Source data?

Many customer projects could benefit from additional data from other sources. However, this comes with its own complications such as:How is it maintained? How is it stored? Are the customers OK with this approach? How is it sourced?

3 days ago

tomtomActive Contributor

Data Science Modelling

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