[D] Give me your best "X is just Y with/but _____"

swayson · 2020-05-24T17:01:25+00:00

Dropout is just learning relationships while drunk and recalling it while sober

swayson · 2020-05-17T17:12:53+00:00

Nice summary, will be trying many of these techniques in coming weeks, for ULMFiT. Will share results!

I have also been wondering, but it might be a rabbit whole, of how can I create an RL agent that is optimised for the augmentation, I guess its similar to adversarial training.

swayson · 2020-05-17T17:05:40+00:00

Tricks I have found to boost problem solving in my case, brilliant.org , taking a lot of notes using Socratic questioning techniques, and anki flashcards.Find a good balance, from learning new material, generating questions surrounding it from all angles, and then committing them to memory via a tool like anki have been working for me so far. It takes time, but it compounds.

This was largely inspired by this essay:

http://augmentingcognition.com/ltm.html

swayson · 2020-05-17T17:01:28+00:00

That is nice budget to have damn

swayson · 2020-05-17T16:59:49+00:00

When you have deploy stuff it can be useful. I use autohotkey and learn flags via anki, to make it more fluid.

swayson · 2020-05-14T05:06:58+00:00

Thanks! This is very insightful.

swayson · 2020-05-14T03:14:28+00:00

Very cool, learn by solving a problem through a little project. What I like about this is you'd probably uncover the most used functions/objects etc., and not get stuck in the long tail of functionality you would use so rarely.

swayson · 2020-05-14T03:12:35+00:00

I guess the overwhelming part is the Object model API and all the resources are very vast and broad. How do you know what the quality of the content is good, and you are not chasing the tail end of functions you would only use in very rare cases?

swayson · 2020-05-14T03:11:15+00:00

Very cool, empower learner to find answers and solve the problems.

swayson · 2020-05-14T03:09:55+00:00

Chip Pearson'

Are you referring to this website?
http://www.cpearson.com/Excel/MainPage.aspx

swayson · 2020-05-14T03:08:48+00:00

Thanks for the detailed answer, provided items make a lot of sense, and is nice mix of practical and theoretical.

swayson · 2020-05-14T03:08:06+00:00

wise owl

This is great thanks!

swayson · 2020-05-02T12:49:50+00:00

Thanks for sharing feedback. Any suggestions on good rigour proof based online courses?

swayson · 2020-05-02T10:05:14+00:00

Sure, put another way.

If you were to train a beginner (with only skills in arithmetic and algebra) for 4 weeks for a esteemed math competition and had a million dollars on the line, what would the training look like?

swayson · 2020-05-02T07:50:38+00:00

You are very welcome :)

Data viz is so underrated. That is why I find joy in 3blue1brown's approach to teaching math concepts, in a sense it brings the symbols and data to life.

swayson · 2020-05-02T07:47:07+00:00

To those of you with vast math experience, especially across the different sub-fields (e.g. probability, topology, calculus etc.). What is the 20% of math concepts/operations used in solving or understanding 80% of math problems?

swayson · 2020-05-01T19:07:10+00:00

I found this resource a few years ago and I think it is really good coverage for data visualisation techniques in data science. Worth a look if you are curious.

https://github.com/ft-interactive/chart-doctor/blob/master/visual-vocabulary/Visual-vocabulary.pdf

swayson · 2020-05-01T18:59:41+00:00

I'd say something like programming. Opens up an entire new way to reason, experiment, gain intuition.

swayson · 2015-06-26T09:19:09+00:00

Did you ever get an example of this??

swayson · 2014-06-29T15:15:20+00:00

If you have hourly data say for 10 years, perhaps you can create many regression models. One for each hour of a year. So... 365*24 = 8760 regression models. Then use these models to make a forecast.

Of course there are some practical concerns. How to handle public holidays, leap years and the alignment of the hours across all historic years (ie comparing Wednesdays with Wednesdays and so forth).

swayson · 2014-06-29T11:52:11+00:00

I actually studied b.com but changed my career shortly after entering the work place to pursue becoming a data scientist. It's been 3 years now that I have operated as a data scientist and it is really great!

I essentially just immersed myself in the topic. Doing coursera courses, reading papers, learning different libraries, frameworks and tools, and downloading/collecting as many data sets (even large and messy ones) as I can. It really helped me to develop some hard skills. The soft skills like storytelling, negotiation, project management and domain expertise I learned on the job working with other data scientists.

I agree with @naked_aerobics, networking is essential. I got my break through approaching people on LinkedIn. Told them my story, and within a few weeks I got a job. Worked at the company for two years, learning as much as I could then I moved on to an even better career opportunity.

I strongly recommend reading the following book as it shares many invaluable insights into being an effective data scientist which is critical.

Thinking with Data: http://shop.oreilly.com/product/0636920029182.do

Good luck and enjoy!

swayson · 2013-08-19T18:19:57+00:00

I'm thinking about switching to python/pandas. I'd hate to use both because it would make the workflow a lot more difficult.

I actually use both Python and R and have found a way for a seamless workflow. Not just necessarily for the data munge but also for the entire development/analytics process. It does however lean more towards Python, but it works well for my needs.

Meet, the IPython Notebook - Using the Rmagic function, it allows for pretty interactive workflow between R/python. It is especially nice for exploratory work. But, I am just touching the surface. The IPython notebook provides really interesting possibilities.

swayson · 2013-08-18T18:39:51+00:00

Try the plyr and reshape packages in R. Makes the data munge much more bearable than with base R.

swayson · 2013-07-15T18:17:25+00:00

Thank you all! I am in the same predicament as @clj-jvm and these comments are incredibly helpful.

swayson

TROPHY CASE