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As per the title I wrote a book called "Managing Machine Learning", it's available as an e-book (https://www.manning.com/books/managing-machine-learning-projects). Here's a blog post about the book:
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Posted by Jason Wei and Yi Tay, Research Scientists, Google Research, Brain Team The field of natural language processing (NLP) has been revolutionized by language models trained on large amounts of text data. Scaling up the size of language models often leads to improved performance and sample efficiency on a range of downstream NLP tasks. In many ...
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Posted by Noah Snavely and Zhengqi Li, Research Scientists, Google Research We live in a world of great natural beauty — of majestic mountains, dramatic seascapes, and serene forests. Imagine seeing this beauty as a bird does, flying past richly detailed, three-dimensional landscapes. Can computers learn to synthesize this kind of visual experience ...
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In this post, we will talk about encoding to be able to use categorical data as features for our ML models. Categorical data has variables that contain label values (text) and not numerical values. We have to convert data which contains categorical variables to numbers before we can train a ML model. Two most popular encoding techniques are Ordinal
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Posted by Rishabh Agarwal, Senior Research Scientist, and Max Schwarzer, Student Researcher, Google Research, Brain Team Reinforcement learning (RL) is an area of machine learning that focuses on training intelligent agents using related experiences so they can learn to solve decision making tasks, such as playing video games, flying stratospheric ...
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Posted by Peter H. Li, Research Scientist, and Sven Dorkenwald, Student Researcher, Connectomics at Google Mapping the wiring and firing activity of the human brain is fundamental to deciphering how we think — how we sense the world, learn, decide, remember, and create — as well as what issues can arise in brain disease or dysfunction. Recent effor ...
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I am about to finish my PhD in machine learning soon. Unfortunately, during my PhD, I became disabled and lost most of the function in my hands and some in my legs. I have been relying on voice-to-code software to do my work, but programming with it is not particularly easy or efficient.
I am looking for industry jobs right now, a ...
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Posted by Jacky Liang, Research Intern, and Andy Zeng, Research Scientist, Robotics at Google A common approach used to control robots is to program them with code to detect objects, sequencing commands to move actuators, and feedback loops to specify how the robot should perform a task. While these programs can be expressive, re-programming polici ...
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I work exclusively in NLP and since the transformers and especially their pretrained type took over, I haven't written a neural nets (RNN, LSTM, etc.) in over 3 years and haven't had to worry about things like # of layers, hidden size, etc.
Tabular data has XGBoost, etc.NLP has Pretained Transformers.Images have Pretrained CNNs, Transformers.
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Hey everyone!
My name's Ryan and I write for the Blog over at AssemblyAI. You might've seen some of my posts on here about things like
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Using Dagshub Direct Data Access and Azure ML SDK, we train a model on Azure without storing data on-prem. We will use the data from Kaggle's, Mayo Clinic — STRIP AI challenge to show how we can stream data in batches from Dagshub Repo saving GPU Cost and Time.
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Hi everybody, here is the complete relabelling of the COCO 2017 dataset for segmentation. This is all free of charge, un-gated, and was done by Sama, a labelling company for CV data. The dataset is available on the Sama website under a Creative Commons license:
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The job of attorneys and law firms is already changing in many ways thanks to artificial intelligence (AI) and machine learning. The applications of legal automation have become more sophisticated, ranging from filtering enormous document review sets during litigation to extracting important terms from contracts in due diligence processes. Anecdote
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Meta recently announced Grand Teton, their next-generation hardware platform for AI training. Grand Teton features several improvements over the previous generation, including 2x the network bandwidth and 4x the host-to-GPU bandwidth. By Anthony Alford
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Hey everyone!
Some friends and I built a twitter bot that explains complicated tweets to you like you're 5 using GPT3. It's free to use. All you have to do is mention @/simplifybot under a tweet and we will translate it for you in a few minutes. https://twitter.com ...
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Hello!
I just hit 1.0.0 version of a library I've been developing for the past months as a side project.
# Pytorch Symbolic
A library that aims to provide a concise API for neural network creation in PyTorch. The API and the inner workings are similar to
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Object detection is a very common task in Computer Vision. YOLOv5s can’t be the best out of the box for every task. It is easy to get best of both worlds - fast detector and accurate classifier. In this case detector can be trained only on damaged road. Classifier is easier to retrain on new data (labelling and training are faster) And this solutio
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Vienna After a longer COVID break we are happy to announce the upcoming ViennaR Meetup on Thursday, November 10! ? ? ? The (live) Meetup is hosted at TU Vienna, the legendary Goldenes Lamm, Seminarraum 107/1 - where some R-Core magic happened. ? REGISTER FOR LIVE MEETUP Note, that this meetup is hybrid and also available ... Continue reading: Vienn
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