This site like many others, uses small files called cookies to help us customise your experience.

Hey, everyone! I'm looking for one or two people to join a small study group to go through the An Introduction to Statistical Learning/ISLR 2nd edition while going through the companion edX course.
We ask that you:
* Commit 5-7hrs of study per week* Consistently go to the weekend study session around 7 or 8am GMT-7* Have the recommended prer ...
be the first to vote
1. Introduction Often times before crucial matches, or in general, we would like to know the performance of a batsman against a bowler or vice-versa, but we may not have the data. We generally have data where different batsmen would have faced different sets of bowlers with certain performance data like ... Continue reading: Player Performance Esti
be the first to vote
Last year Google introduced Cloud TPU Virtual Machines (VMs), which provide direct access to TPU host machines in preview. Today, Cloud TPU VMs are generally available, including the new TPU Embedding API, which can accelerate ML Based ranking and recommendation workloads. By Steef-Jan Wiggers
be the first to vote
Monte Zweben proposes a whole new approach to MLOps that allows to scale models without increasing latency by merging a database, a feature store, and machine learning. By Monte Zweben
be the first to vote
Researchers at Google subsidiary DeepMind and the Swiss Plasma Center at EPFL have developed a deep reinforcement learning (RL) AI that creates control algorithms for tokamak devices used in nuclear fusion research. The system learned control policies while interacting with a simulator, and when used to control a real device was able to achieve nov
be the first to vote
Photo by Luca Bravo on Unsplash Create your custom model and upload it on Hugging Face Introduction Often when we want to solve an NLP problem, we use pre-trained language models, obviously being careful to choose the most appropriate model that has been fine-tuned on the language of our interest. For example, if I’m working on a project that is ba ...
be the first to vote
Machine learning assisted computation of the marginal likelihood Bayesian model comparison provides a principled statistical framework for selecting an appropriate model to describe observational data, naturally trading off model complexity and goodness of fit. However, it requires computation of the Bayesian model evidence, also called the margina ...
1 Views
Using Hugging’s Face transformers library and Layer ai to fine tune GPT2 for text summarization Photo by Aaron Burden on Unsplash The Transformer soon became the most popular model in NLP after its debut in the famous article Attention Is All You Need in 2017. The capacity to analyze text in a non-sequential manner (as opposed to RNNs) enabled larg ...
1 Views
Introduction and solution to Feynman’s Restaurant Problem from a RecSys perspective Photo by shawnanggg on Unsplash You’re on holiday, and you’re going to spend the following days on a remote island in the Pacific. There are several restaurants and you would like to enjoy the most the local cuisine. The problem you face is that a priori you don’t k ...
1 Views
Three methods to detect outliers, with examples in Python Photo by Will Myers on Unsplash At the beginning of a Data Science project, one important part is outlier detection. When we perform Exploratory Data Analysis, in fact, one of the things to do is to find outliers and treat them, in some ways. In this article, we will see three methods to det ...
1 Views
Hot off the tail of Flamingo, DeepMind has released a report describing a generalist learning agent that works across disparate tasks.
Very cool stuff, was hoping to get some discussion on it.
Here is their abstract:
Inspired by progress in large-scale language modelling, we apply a similar approach towards building a single generalist age ...
be the first to vote
I am happy to announce The Fast Deep RL Course.
This course is made for Data Scientists/ML engineers who are excited about Deep Reinforcement Learning and are looking for a **short and practical introduction to the topic**.
This course covers every ...
be the first to vote
Diffusion Models have gained some impressive ground in the past couple of years, including famously overtaking GANs on image synthesis and being used in DALL-E 2.
**I wrote this** **introduction to diffusion model ...
be the first to vote
Take the first R steps and enhance your data science toolkit with us on June 8th! Would you like to discover the basics of R programming and get solid foundations for future learning? Even if you are an absolute beginner, the workshop “R basics - ob... Continue reading: ‘R basics – objects, functions and operations’ workshop
1 Views
Whenever I look at Kaggle code for machine learning, 90% of the code is just reading data. Not a lot of lines are actually devoted towards setting the hyper parameters, the optimization algorithm, and the architecture. Whenever someone thinks of machine learning, people tend to think of intensive coding, but it seems that the coding aspect is not t ...
be the first to vote
Posted by Isaac Caswell and Ankur Bapna, Research Scientists, Google Translate Machine translation (MT) technology has made significant advances in recent years, as deep learning has been integrated with natural language processing (NLP). Performance on research benchmarks like WMT have soared, and translation services have improved in quality and ...
be the first to vote