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Ask Me Anything (AMA)

Thu, 7 Jul, 11:00

Ask Me Anything (AMA) with Katie King

Conference

Thu, 6 Oct, 8:00

AltitudeX MCR | The Decision Intelligence Summit

liammccaffrey

started this topic

Ask Me Anything: Atul Sharma

Join Atul Sharma, chief technology officer (CTO) at Peakfor our next Ask Me Anything (AMA) session When: Thursday 19 May 2022 at 12:00 BSTWh...

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...

Recent activity

debstCommunity Member

Getting started

Data Science internships/apprenticeship

Hi Team,I am currently pursuing Masters in Data Science at the University of Manchester and due to graduate in September-2022. I am looking for a DS internship to grasp the real-world problem-solving aspect of Data Science. I have some knowledge of it as part of assignments and coursework, but that’s not enough to get me started or be hired for a direct recruit role in Data Science. I want to experience hands-on training and land a Graduate/Junior role in the same, which can be possible via an internship. Kindly let me know if Peak offers any remote internships or similar learning opportunities.Looking forward to learning more,Thanks and regards,Debashree Tripathy

13 hours ago

liammccaffreyCommunity Manager

2022

Ask Me Anything: Katie King

Live on Thursday 7 July 2022 at 12:00 BST Katie King is a published author, keynote speaker, trainer and consultant on Artificial Intelligence (AI), digital, STEM, leadership and business transformation.Katie has over 30 years of consulting experience and has advised many of the world's leading brands and business leaders.AuthorHer first book, Using Artificial Intelligence in Marketing: How to Harness AI and Maintain the Competitive Edge, was translated into Russian, Chinese, Vietnamese & other languages. It was also listed as a reference source in the 'brand strategy' section of the World Economic Forum's Empowering AI Leadership AI toolkit for corporate boards.Her second book was published by Kogan Page in January 2022: AI Strategy for Sales and Marketing: Connecting marketing, sales and customer experience.AdvisorKatie is a member of the UK Government All-Party Parliamentary Group (APPG) task force for the adoption of AI. She is also an Editorial Board Member for the AI and Eth

16 hours ago

EvolvingRichieActive Contributor

Communication and Visualization

Is there any meaningful difference between an AB test and a scientific experiment?

Is the data science term “AB test” just a rebranding of what scientists have been calling “an experiment” for hundreds of years?

17 hours ago

ruaridhgeorgeFrequent Visitor

Q&A

Biggest mistake whilst learning data science

I’d like to hear everyone’s biggest mistake, regret or oversight as they were learning data science. Hopefully we can learn from eachother’s experiences and help people currently starting to learn data science!

3 days ago

EvolvingRichieActive Contributor

Recomendation: Excellent book on data cleaningNew

Most of the way through “The beginners guide to clean data” and loving it! Such a broad book, covering all aspects of data cleaning. Written in short, clear, digestible sections.There’s a free version here, but you can buy an E-book copy (which I did the support the author, it’s just that good)https://b-greve.gitbook.io/beginners-guide-to-clean-data/

3 days ago

ChrisBillinghamCommunity Manager

Q&A

What's the one thing you wish you knew?

Looking back on your career as a DS and how you got into the role, whats the one thing you wish you knew right at the start that would’ve made becoming the amazing DS you are now easier?

6 days ago

FazilActive Contributor

Data Science Modelling

Monte Carlo Simulations

Consider a scenario where you're expected to solve a very tricky probability problem but you don't know how to solve it or another scenario where the probability problem requires a specific domain knowledge in which you're not an expert. Monte Carlo Simulation will come to your rescue in such scenarios, it is a method in which we simulate the random experiment using computational algorithms. It is usually a much simpler method to find the required probability compared to the theoretical (or mathematical) methods, however it is not as accurate as the mathematical method and it can be slow & computationally expensive.Lets understand Monte Carlo Simulation using examples!Lets start with one of the simplest and most commonly sited example of Monte Carlo Simulation and once we get a hang of it. We'll solve a tricky problem using the same technique.https://www.linkedin.com/posts/fazil-mohammed-4062711b2_monte-carlo-simulations-activity-6945626961729712128-tcgU?utm_source=linkedin_share

6 days ago

liammccaffreyCommunity Manager

2022

Ask Me Anything: Helen Craven

Live on Tuesday 21 June 2022 at 12:00 BST Ask Me Anything with Helen Craven, graduate data scientist at Peak. joins us for an Ask Me Anything (AMA) session. Introducing our guest: Helen Craven You’ve qualified, motivated and ready to be a data scientist. But how do you land your first role? Helen Craven is here to help.Helen joined Peak as a graduate data scientist just over two months ago and she’s been doing great things with data ever since. She’s the perfect person to put your early career data science questions to.How do you find entry-level roles? What does a great data science CV look like? Whatever your question, join Helen at 12:00 BST on Tuesday 21 June 2022 to ask her anything. Submit your questions Whatever your question, you can submit your questions now below and then join us on Tuesday 21 June 2022 to be a part of the discussion.

8 days ago

tomtomActive Contributor

Data Science Modelling

Forecasting is Snow Joke

12 days ago

FazilActive Contributor

Centroid Vs Geometric MedianNew

In clustering algorithms like K-Means there's a commonly quoted example which goes as follows. Imagine there are 5 clusters of people, as a business owner we need to open 5 new food joints in order to cater to these people. K-Means helps us in strategically placing our food joints in such locations so as to reduce the overall time spent by these people to commute to the nearest joint (For simplicity, we're going to ignore the fact that the path between any 2 points in real world is rarely a straight line).Though this helps us a great deal to wrap our head around the concept of K-Means, it is technically wrong. Centroid minimizes the sum of squares of distances of all the points from it which is not equivalent to minimizing the sum of distances of all the points from it. The point which minimizes the sum of distances of all the points from it is called the geometric median. Centroid (or mean) is very easy to compute, we just have to add all the points (vector addition) and divide it by

12 days ago

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