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Career Advices

Focus.

Be patient.

Stay Humble.

Listen & Learn.

Influence people around you.

Make life worthy living.

Stay on a path.

Focus on your strengths.

Listen to your users.

Optimize for simplicity.

Prioritize ruthlessly.

Underpromise, overdeliver.

Be calm and confident (Always Smile).

Be aware of your blindspots.

Don’t worry about things you cannot change.

Make everything measurable.

Taking care of yourself first.

Focus on Measurable Impact.

Views humility collectively.

Always ask: What can I do for you today?

What gets measured, gets done.

Work with people who you can learn from.

Good leaders are willing to be hated.

Always put the other person 1st and say foo and I. 

Perfect is the enemy of good.

Collect feedback early.

Manage expectations often and early.

Don’t Criticize, Condemn or Complain.

Always face yourself honestly and continue to polish.

Let your manager speak, explain their expectations.

Say what people need to know. Do not say more than you need to.

Strive to align “skills, interest and opportunity”, take the long view.

If you think a problem is too big for you, go do it anyway.

Be a team player and do what your lead asks you to do.

When in disagreement, first thank someone for what they are doing and then question them.

Do not be attached to code because of how much effort you put into it. Bad code needs to be discarded.

One finger pointing at the other person, three fingers pointing back at us.

I am doing a great job, I am calm and at peace, I am good enough, I am perfect at this moment.

When angry, count to 10 before you speak. If very angry, a hundred.

Do not be attached to code because of how much effort you put into it. Bad code needs to be discarded.

One finger pointing at the other person, three fingers pointing back at us.

I am doing a great job, I am calm and at peace, I am good enough, I am perfect at this moment.

When angry, count to 10 before you speak. If very angry, a hundred.

A can-do optimistic attitude needs to be tempered with a critical look at project goals and timelines.

For junior engineers, don’t limit yourself to a predefined model, say “I will see what can be done” when asked to help.

Be clear and concise about what you want your audience to know.

Play to your strengths, and work on things that you care about. Focus on doing the right thing, and the rest will follow.

We can only see a short distance ahead, but we can see plenty there that needs to be done.

Take care of all challenging/annoying tasks at the beginning of the day.

In reality, there is no such thing as a perfect solution. acknowledge the risks in what we do not know, and make the best decision from there.

Reference:

Manager and Employee Feedback Examples: How To Give Feedback at Work https://www.leapsome.com/blog/manager-and-employee-feedback-examples-how-to-give-feedback-at-work Learn about Google’s manager research https://rework.withgoogle.com/guides/managers-identify-what-makes-a-great-manager/steps/learn-about-googles-manager-research/

Free Resources for Everyone During COVID-19 Outbreak

To everyone, 

Hope you and your loved ones will find resources listed below useful. Stay safe, and we will get through this together!

Stay HealthyStay Creative Stay ConnectedStay Hungry, Stay Foolish
https://donottouchyourface.com/

Free Workout Trainings
https://www.onepeloton.com/app
https://www.corepoweryogaondemand.com/keep-up-your-practice
https://www.youtube.com/user/CosmicKidsYoga

Free Mental Wellbeing Tips
https://hbr.org/2020/03/build-your-resiliency-in-the-face-of-a-crisis?utm_source=twitter&utm_campaign=hbr&utm_medium=social
https://suicidepreventionlifeline.org/current-events/supporting-your-emotional-well-being-during-the-covid-19-outbreak/
Free Art
https://www.brit.co/free-classes-stay-creative/
https://www.buzzfeed.com/andyneuenschwander/13-museums-you-can-visit-online-during-your-quarant

https://www.travelandleisure.com/attractions/museums-galleries/museums-with-virtual-tours?utm_medium=social&utm_term=59F3F59E-653B-11EA-938E-3D9296E8478F&utm_source=facebook.com&utm_campaign=travelandleisure_travelandleisure&utm_content=link&fbclid=IwAR1oFVBt47HiQ1ZaJSOvxOsS-ocrytmBnh976RpzdpKgW8jpPeUCiAzcpJE

Free Music
https://www.wkar.org/post/list-live-streaming-concerts#stream/0
https://operawire.com/metropolitan-opera-to-offer-up-nightly-met-opera-streams/
Free Hangout Apps
https://duo.google.com/
https://hangouts.google.com/
https://jamm.app/en/
https://zoom.us/
Strategies for online learning/teaching
https://teachfromhome.google/intl/en/
https://globalonlineacademy.org/insights/articles/15-strategies-for-online-learning-when-school-is-closed
https://podcast.concordiashanghai.org/blog/2020/02/21/tech-talk-roundtable-07-14-when-virtual-learning-is-your-only-option/
https://www.nextvista.org/advice/continuity/index.phtml
https://campusadvisories.gwu.edu/tools-instructional-continuity

Free Books
https://www.mountainview.gov/depts/library/catalogsearch/ebooks.asp
https://www.audible.com/
https://www.getepic.com/

Free Education
For age 3~18 learners :
https://www.instagram.com/play.hooray/?hl=en
https://classroommagazines.scholastic.com/support/learnathome.html
https://outschool.com/
https://www.headspace.com/meditation/kids
https://pbskids.org/
https://www.pbs.org/parents/pbskidsdaily?source=email
https://mysteryscience.com/school-closure-planning
https://learn.khanacademy.org/khan-academy-kids/
https://www.brainpop.com/
https://www.kennedy-center.org/education/mo-willems/
https://signup.toucanbox.com/gb/choose
https://www.kiwico.com/
https://tinkerlab.com/
http://madebyjoel.com/madetoplay
https://creativepark.canon/en/special/kids4-7yrs/index.html

For age 18+ learners
https://www.youtube.com/channel/UCtFRv9O2AHqOZjjynzrv-xg
https://newsela.com/
https://www.youtube.com/results?search_query=%23cv19ReadAloud
https://ed.ted.com/
http://epgy.stanford.edu/

Free Podcasts
https://www.storypirates.com/podcast
https://www.npr.org/podcasts/474377890/but-why-a-podcast-for-curious-kids
https://www.npr.org/podcasts/510321/wow-in-the-world
https://www.brainson.org/
http://andrewandpolly.com/earsnacks
https://www.npr.org/podcasts/532788972/circle-round
http://storiespodcast.com/
https://gimletmedia.com/shows/the-two-princes
https://anchor.fm/professortheo
http://www.bestrobotever.com/pants-on-fire
https://www.brainson.org/pages/smashboombest

What is the Difference Between Test and Validation Datasets?

– Training set: A set of examples used for learning, that is to fit the parameters of the classifier.

– Validation set: A set of examples used to tune the parameters of a classifier, for example to choose the number of hidden units in a neural network.

– Test set: A set of examples used only to assess the performance of a fully-specified classifier.

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Causality in machine learning

Given recent advances and interest in machine learning, those of us with traditional statistical training have had occasion to ponder the similarities and differences between the fields. Many of the distinctions are due to culture and tooling, but there are also differences in thinking which run deeper. Take, for instance, how each field views the provenance of the training data when building predictive models. For most of ML, the training data is a given, often presumed to be representative of the data against which the prediction model will be deployed, but not much else. With a few notable exceptions, ML abstracts away from the data generating mechanism, and hence sees the data as raw material from which predictions are to be extracted. Indeed, machine learning generally lacks the vocabulary to capture the distinction between observational data and randomized data that statistics finds crucial. To contrast machine learning with statistics is not the object of this post (we can do such a post if there is sufficient interest). Rather, the focus of this post is on combining observational data with randomized data in model training, especially in a machine learning setting. The method we describe is applicable to prediction systems employed to make decisions when choosing between uncertain alternatives.

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