June 2022

Haskell in Production: Channable

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In our Haskell in Production series, we interview developers from companies that use Haskell for real-world tasks. We cover benefits, downsides, common pitfalls, and tips for new Haskellers. Our today’s guest is Fabian Thorand, who is a team lead at Channable. Read further to learn where Channable uses Haskell, why they chose it, and what they like and don’t like about it. Interview with Fabian Thorand Could you tell us a little bit about Channable and your role […]

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Random Forest Classifier: Basic Principles and Applications

Random Forest Classifier: Basic Principles and Applications

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Predicting customer behavior, consumer demand or stock price fluctuations, identifying fraud, and diagnosing patients – these are some of the popular applications of the random forest (RF) algorithm. Used for classification and regression tasks, it can significantly enhance the efficiency of business processes and scientific research. This blog post will cover the random forest algorithm, its operating principles, capabilities and limitations, and real-world applications. What is a random forest? A random forest is a supervised machine learning algorithm […]

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Functional Futures: Grain with Oscar Spencer

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In this month’s episode of Functional Futures, our guest is Oscar Spencer – a co-author of a functional programming language called Grain that compiles to WebAssembly. Listen to the episode to learn more about Grain, WebAssembly, and how to sell functional programming to developers. You can check out the full episode on our YouTube channel or listen to the audio version on our podcast page. Below, you can find some of the highlights of the episode, edited for […]

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A Beginner’s Guide to Data Mining Techniques

A Beginner’s Guide to Data Mining Techniques

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A Beginner’s Guide to Data Mining Techniques Data mining techniques have applications in all areas from business to science and governance. Companies use data mining to analyze recorded data, such as user preferences, sales figures, and historical inventory levels. If they are able to identify trends and recurrent patterns in this data, they can make better decisions. When managed properly, this information can become an effective tool to drive brand awareness, product development, and marketing initiatives, and strengthen […]

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ACL 2022 Highlights

ACL 2022 Highlights

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ACL 2022 took place in Dublin from 22nd–27th May 2022. This was my first in-person conference since ACL 2019. This is also my first conference highlights post since NAACL 2019. With 1032 accepted papers (604 long, 97 short, 331 in Findings), this post can only offer a glimpse of the diverse research presented at the conference—biased towards my research interests. Here are the themes that were most noticeable for me across the conference program: Language Diversity and Multimodality […]

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Predicting Generalization using GANs

Predicting Generalization using GANs

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A central problem of generalization theory is the following: Given a training dataset and a deep net trained with that dataset, give a mathematical estimate of the test error. While this may seem useless to a practitioner (“why not just retain some holdout data for testing?”), this is of great interest to theorists trying to understand what properties of the net or the training algorithm lead to good generalization. Old posts on this blog such as this one […]

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