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Trustworthy AI How do you ensure your model is fair from start to finish? Russell Holz contributed to this article. Photo by Gio Bartlett on Unsplash In the first blog post of this series, we discussed three key points to creating a comprehensive fairness workflow for ensuring fairness for machine learning model outcomes. They are: identifying bias ...
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What are disentangled representations? How can we learn disentangled representations for any arbitrary model using flow-based generative models? Fig. 1: The IIN network can be applied to arbitrary existing models. IIN takes the representation z, learned by the arbitrary model and factorised it into smaller factors such that each factor learns to re ...
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Simple Online Learning Algorithm One of the most basic yet powerful online learning algorithms in literature. Image by Author Why Recursive Least Squares? Online learning is a booming field of research in the AI research space. Many problems in today's world require machines to learn on the fly and improve or adapt as they collect new information. ...
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An overview of online learning techniques, focusing on those that are most effective for the practitioner. In this blog post, I will take a deep dive into the topic of online learning — a very popular research area within the deep learning community. Like many research topics in deep learning, online learning has wide applications in the industrial ...
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I don't get how that's acceptable. Repo is proudly and prominently linked in the paper, but it's empty. If you don't wanna release it, then don't promise it.
Just wanted to rant about that.
I feel like conferences should enforce a policy of "if code is promised, then it needs to actually be public at the time the proceedings are published, ot ...
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Exploring statistics using Calculus Hi Everyone, This is about the mathematics that is used in the linear regression (with gradient descent) algorithm. This was a part of my IB HL Mathematics Exploration. Linear Regression: What is it? Linear Regression is a statistical tool that produces a line of best fit for a given dataset analytically. To prod ...
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Article https://www.businessinsider.com/deepmind-secret-plot-break-away-from-google-project-watermelon-mario-2021-9
by Hugh Langley and Martin Coulter
> For a while, some DeepMind employees referred to it as "Watermelon." Later, executives called it "Mario." Both code names meant the same thing: a secret plan to break away from parent company ...
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I'm the head of data science at a big company. One of the sub-teams recently hired a graduate of a data science boot camp. He's good at writing queries, picking the right algorithm for a problem, etc. The problem is he doesn't know the technical basics of working on a team. He commits to production without testing locally, refers to files using abs ...
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I work as a Data Scientist as a small (but somewhat successful) consultancy firm.
After a few failures, we've managed to deliver in the past years quite a number of successful projects with clients. But we (and me in particular, as the DS that's been here the longest) are starting to have a bit of a scaling up problem:
\- We have models ever ...
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>This is a series of posts that I post almost daily. I call them “your daily dose of machine learning”.
How do you deploy your deep learning model on google cloud?
When you’re done training a model, the deployment part starts.
A lot of companies deploy their models on the cloud because it’s easier to scale that way.
In google cloud th ...
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Posted by Mingxing Tan and Zihang Dai, Research Scientists, Google Research As neural network models and training data size grow, training efficiency is becoming an important focus for deep learning. For example, GPT-3 demonstrates remarkable capability in few-shot learning, but it requires weeks of training with thousands of GPUs, making it diffic ...
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Context: I'm reacquainting myself with literature for semi-supervised learning and basically every recent paper claims state of the art results against the exact same baselines. Logically, though, that means that I have no way of knowing which methods actually *are* effective. I'm lucky to have had several years of experience that provided intuitio ...
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Posted by Vighnesh Birodkar, Research Software Engineer and Jonathan Huang, Research Scientist, Google Research Instance segmentation is the task of grouping pixels in an image into instances of individual things, and identifying those things with a class label (countable objects such as people, animals, cars, etc., and assigning unique identifiers ...
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Hello everyone, I am looking for people who are interested in learning more about machine learning and reinforcement learning. I am currently at a financial institution working on a reinforcement learning project for the past year and I am looking to get some practice with teaching **(FREE)**! If you are currently in school, or just looking to lear ...
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It is springtime in Eastern Washington, USA, and the temperature is slightly above freezing. A farmer is preparing to fertilize his fields of wheat and lentils as winter runoff and frost are nearly finished. The plants are susceptible to fertilizer at freezing temperatures, so the farmer checks forecasts from the local weather station, which is […]
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PyTorch Tutorial: A Complete Use-case Example Introduction This tutorial shows a full use-case of PyTorch in order to explain several concepts by example. The application will be hand-written number detection using MNIST. MNIST is a popular (perhaps the most popular) educational computer vision dataset. It is composed of 70K images of hand-written
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From ICLR 2022's website: https://iclr.cc/Conferences/2022/CallForBlogPosts
*This year, the ICLR 2022 main conference will host a blog post track. We invite both academic and industrial researchers to submit their posts on a previously ...
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Ogive curve in R, It is a graph plotted for the variate values and their corresponding cumulative frequencies of a frequency distribution. The sum of all preceding frequencies up to this point is referred... The post Ogive curve in R appeared first on finnstats. Continue reading: Ogive curve in R
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