Open in app

Sign In

Write

Sign In

Ludovic Benistant
Ludovic Benistant

6.1K Followers

Home

About

Published in Towards Data Science

·Jun 4, 2021

Get Started With Bayesian Statistics

Want to learn about the world of Bayesian statistics and better understand the difference between Bayesian and frequentist methods? Psychologist and consultant Hannah Roos wrote the resource you’ve been looking for. After introducing the necessary terms, Hannah dives into a brilliant case study (involving weddings and weather!) that makes these concepts come alive. If you want to know when, why, and how you should use Bayesian statistics, this article is for you.

Data Science

1 min read

Data Science

1 min read

EXPLORING DATA SCIENCE

Get Started With Bayesian Statistics

Want to learn about the world of Bayesian statistics and better understand the difference between Bayesian and frequentist methods? Psychologist and consultant Hannah Roos wrote the resource you’ve been looking for. After introducing the necessary terms, Hannah dives into a brilliant case study (involving weddings and weather!) that makes these concepts come alive. If you want to know when, why, and how you should use Bayesian statistics, this article is for you.

Better Done Bayesian?

Planning our wedding party with Bayesian - vs. Frequentist statistics.

towardsdatascience.com

--

--


Published in Towards Data Science

·May 21, 2021

What is Likelihood-Free Inference, and What Are Its Use Cases?

Advances in likelihood-free inference and meta-learning made Arthur Pesah (PhD student in quantum computing at UCL) and Antoine Wehenkel (PhD Student at Belgium’s National Fund for Scientific Research) wonder: “Can we build a machine that takes a tweakable simulator and real data as input, and returns the version of the simulator that fits best some real data?” Read this eye-opening article to find out what they discovered. It offers multiple GIFs and graphs to ease your exploration of these complex concepts.

Data Science

1 min read

Data Science

1 min read

EXPLORING DATA SCIENCE

What is Likelihood-Free Inference, and What Are Its Use Cases?

Advances in likelihood-free inference and meta-learning made Arthur Pesah (PhD student in quantum computing at UCL) and Antoine Wehenkel (PhD Student at Belgium’s National Fund for Scientific Research) wonder: “Can we build a machine that takes a tweakable simulator and real data as input, and returns the version of the simulator that fits best some real data?” Read this eye-opening article to find out what they discovered. It offers multiple GIFs and graphs to ease your exploration of these complex concepts.

Improve your scientific models with meta-learning and likelihood-free inference

Introduction to likelihood-free inference and distillation of the paper Recurrent Machines for Likelihood-Free…

towardsdatascience.com

--

--


Published in Towards Data Science

·May 8, 2021

Want a Challenging but Rewarding Read? Explore the Technical Approaches to Mitigating Algorithmic Bias

Now that the machine learning community has recognized the need to take algorithmic bias seriously, it’s time to explore potential ways to mitigate it — including algorithmic solutions. In this article, former DeepMind Research Engineering intern Joyce Xu asks, “how, algorithmically, can we ensure that the models we build are…

Data Science

1 min read

Data Science

1 min read

EXPLORING DATA SCIENCE

Want a Challenging but Rewarding Read? Explore the Technical Approaches to Mitigating Algorithmic Bias

Now that the machine learning community has recognized the need to take algorithmic bias seriously, it’s time to explore potential ways to mitigate it — including algorithmic solutions. In this article, former DeepMind Research Engineering intern Joyce Xu asks, “how, algorithmically, can we ensure that the models we build are…

--

--


Published in Towards Data Science

·Apr 17, 2021

Interested in Decision Intelligence? Start Here

“Decision intelligence is the discipline of turning information into better actions at any scale.” In this comprehensive 14-minute read, Cassie Kozyrkov, Head of Decision Intelligence at Google, invites us to learn more about her field of expertise. After introducing important terminology and concepts — from “what’s a decision” to “what’s the difference between making a calculation versus making a decision” — Cassie digs deeper into this fascinating topic and demonstrates how relevant it is for the work of all data scientists.

Data Science

1 min read

Data Science

1 min read

Exploring Data Science

Interested in Decision Intelligence? Start Here

“Decision intelligence is the discipline of turning information into better actions at any scale.”

In this comprehensive 14-minute read, Cassie Kozyrkov, Head of Decision Intelligence at Google, invites us to learn more about her field of expertise. After introducing important terminology and concepts — from “what’s a decision” to “what’s the difference between making a calculation versus making a decision” — Cassie digs deeper into this fascinating topic and demonstrates how relevant it is for the work of all data scientists.

What is Decision Intelligence?

A new discipline for leadership in the AI era

towardsdatascience.com

--

--


Published in Towards Data Science

·Apr 10, 2021

Common Distance Measures Simply Explained

Distance measures are ubiquitous in data science and machine learning. Many algorithms rely on them, and “knowing when to use which distance measure can help you go from a poor classifier to an accurate model.” In this article, Maarten Grootendorst does a fantastic job explaining the most common ones. For each of the nine distance measures, Maarten describes how they work, offers several use cases, and discusses their potential drawbacks.

Deep Dives

1 min read

Deep Dives

1 min read

Exploring Data Science

Common Distance Measures Simply Explained

Distance measures are ubiquitous in data science and machine learning. Many algorithms rely on them, and “knowing when to use which distance measure can help you go from a poor classifier to an accurate model.” In this article, Maarten Grootendorst does a fantastic job explaining the most common ones. For each of the nine distance measures, Maarten describes how they work, offers several use cases, and discusses their potential drawbacks.

9 Distance Measures in Data Science

The advantages and pitfalls of common distance measures

towardsdatascience.com

--

--


Published in Towards Data Science

·Oct 20, 2020

Contribute to Towards Data Science

Hey everyone! Since we frequently receive questions about how to contribute to TDS, I’ve gathered some thoughts that I hope will help those interested in getting started. First and foremost, we have put a lot of effort into our Write for Towards Data Science article. If you haven’t looked at…

Writing

2 min read

Contribute to Towards Data Science
Contribute to Towards Data Science
Writing

2 min read


Published in Towards Data Science

·Dec 14, 2016

Is Data Science A Real Science?

As I hear criticisms about how data science is unscientific, I would like to clarify what is science, and to show how data scientists can answers these common criticisms about their field. — What is science? Science is a quest to reach good explanations about the world. As David Deutsch pointed out in his book, The Beginning of Infinity, a good explanation is clear, precise and hard to vary. What is data science?

Data Science

4 min read

Is Data Science A Real Science?
Is Data Science A Real Science?
Data Science

4 min read

Ludovic Benistant

Ludovic Benistant

6.1K Followers

Editor and curator at Towards Data Science

Following
  • Ryan Xu

    Ryan Xu

  • Kerry Halupka

    Kerry Halupka

  • Dea Bardhoshi

    Dea Bardhoshi

  • Hurmet Noka

    Hurmet Noka

  • LucianoSphere

    LucianoSphere

Help

Status

Writers

Blog

Careers

Privacy

Terms

About

Text to speech