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James

@le_james94

27 Apr

My favs:
- Under-promise and over-deliver
- Work where there are no words for what you do
- The reward for good work is more work
- Aim to have others respect you
- Being wise means having more questions than answers
- Compliment people behind their back👇
kk.org/thetechnium/99…

- You are only as young as the last time you changed your mind
- Be strict with yourself and forgiving of others
- Calm is contagious
- Always cut away from yourself
- Measure twice, cut once
- Work for something much larger than yourself 👇

- Sleep is what you desperately need
- Writing down one thing you are grateful for each day is the cheapest possible therapy ever
- Being poor is an advantage in innovation
- Avoid hitting the snooze button
- Always say less than necessary👇

Read 5 tweets

James

@le_james94

17 Apr

@AdamMGrant

Recently finished reading @AdamMGrant so I decided to jot down these practical takeaways to improve my rethinking skills. Might be relevant to you as well! 👇

1 - Think Like A Scientist:

When forming an opinion, resist the temptation to preach, prosecute, or politick. Treat your emerging view as a hunch or a hypothesis and test it with data.

2 - Define Your Identity In Values, Not Opinions:

See yourself as someone who values curiosity, learning, mental flexibility, and searching for knowledge. Keep a list of factors that would change your mind.

Read 21 tweets

James

@le_james94

14 Apr

@scale_AI

1/ My notes from @scale_AI Transform✍️It covers:
- Building good data
- Future of ML frameworks
- Challenges for scalable deployment
- How to assess ML maturity

Thanks @alexandr_wang and team for organizing the best AI conference of 2021 thus far. Enjoy!

jameskle.com/writes/scale-t…

@AndrewYNg

2/ @AndrewYNg: "The single most important thing that an MLOps team needs to do is to ensure consistently high-quality data throughout all stages of the ML project life cycle."

@fchollet

3/ @fchollet
The 4 #DeepLearning Trends That Keras Will Support:
- An Ever-Growing Ecosystem of Reusable Parts
- Increasing Automation
- Large-Scale Workflows In The Cloud
- Real-World Deployment

Read 13 tweets

James

@le_james94

25 Aug 20

@Stanford

~ New Post ~

During this quarantine time, I binge-watched @Stanford #CS330 lectures taught by the brilliant @chelseabfinn. This blog post is a summary of the key takeaways on #Bayesian Meta-Learning that I’ve learned. #AtHomeWithAI

medium.com/cracking-the-d…

(1/7) 👇

Bayesian meta-learning generates hypotheses about the underlying function, samples from the data distribution, and reasons about model uncertainty. It is suitable for problems in safety-critical domains, exploration strategies for meta-RL, and active learning.

(2/7) 👇

@drfeifei

There are various Bayesian Meta-Learners pre-neural-nets:

- @drfeifei, @rob_fergus, and @PietroPerona: vision.stanford.edu/documents/Fei-…
- @rsalakhu, @wise_tbaum, and Torralba: proceedings.mlr.press/v27/salakhutdi…
- @LakeBrenden, @rsalakhu, and @wise_tbaum: papers.nips.cc/paper/5128-one…

(3/7) 👇

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