CareerFair - Day-to-day as an Applied Scientist at Amazon
What's an average day like? What's great about the role? How's working in Amazon?
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What's an average day like? What's great about the role? How's working in Amazon?
For years I've refined my routines and found tools to manage my time. Here I share it with readers.
My tools for organization and creation, autopilot routines, and Maker's schedule
A step-by-step of how to migrate from json comments to Utterances.
Checking for correct implementation, expected learned behaviour, and satisfactory performance.
We’ve applied reinforcement learning from human feedback to train language models that are better at summarization.
Should I switch from a regex-based to ML-based solution on my application?
My chat with James Le about my experience, leadership, agile, ML in production, writing, and more.
Why read papers, what papers to read, and how to read them.
Becoming a senior after three years and dealing with imposter syndrome.
How not to become an expert beginner and to progress through beginner, intermediate, and so on.
Examining the broad strokes of NLP progress and comparing between models
Why (and why not) be more end-to-end, how to, and Stitch Fix and Netflix's experience
Updating our FastAPI app to let users select options and download results.
Surprising lessons I picked up from the best books, essays, and videos on writing non-fiction.
Why OMSCS? How can I get accepted? How much time needed? Did it help your career? And more...
I couldn't find any guides on serving HTML with FastAPI, thus I wrote this to plug the hole on the internet.
Ever revisit a project & replicate the results the first time round? Me neither. Thus I adopted these habits.
It's not enough to have a good strategy and plan. Execution is just as important.
I wanted to add my recent writing to my GitHub Profile README but was too lazy to do manual updates.
Our third class of OpenAI Scholars presented their final projects at virtual Demo Day, showcasing their research results from over the past five months.
I thought giving it my all led to maximum outcomes; then I learnt about the 85% rule.
Part II of the previous write-up, this time on applications and frameworks of Spark in production
Sharing my notes & practical knowledge from the conference for people who don't have the time.
After this article, we'll have a workflow of tests and checks that run automatically with each git push.
Does DS have business requirements? When does it make sense to split DS and DE??
We’re excited to announce that OpenAI is co-organizing two NeurIPS 2020 competitions with AIcrowd, Carnegie Mellon University, and DeepMind, using Procgen Benchmark and MineRL.