Eric Weinstein
where else to find them
website:http://ericweinste.in/
github:ericqweinstein
linkedin:ericqweinstein
speakerdeck:ericqweinstein
what they talk about
all 10 in the filters
where they keep going back
all 7 in the filters
on a stage with
- Julian Chealonce
who talks about the same things
- Peter McCormack15 talks
- Adam Back28 talks
- Pete Rizzo16 talks
- Mark Moss18 talks
- Paul Sztorc21 talks
- Jeff Booth13 talks
| title | conference | date |
|---|---|---|
| Functional Programming in Plain Terms | RailsConf 2022 | 2022-05-17 |
Walks through concrete examples: Haskell type signatures like head :: [a] -> Maybe a, shows how fmap maps to Ruby map, and demonstrates accumulation with… | ||
| Interview Them Where They Are | RailsConf 2019 | 2019-05-01 |
Argues that technical interviewing is broken and prescribes concrete fixes: refactor job descriptions to state required stack and success metrics (example… | ||
| Value Your Types! | !!Con West 2019 | 2019-03-25 |
Types encode concrete properties now: dependent types express “non‑negative” or “length‑N” constraints, shown with Idris vectors where the type carries the… | ||
| Being Good: An Introduction to Robo- and Machine Ethics | RubyConf 2018 | 2018-11-28 |
Three concrete failure modes decide whether to watch: a medical irradiator (Therac-25) replaces hardware interlocks with assembly code and concurrent bugs and… | ||
| What If... ?: Ruby 3 | RubyConf 2017 | 2017-11-15 |
Explores three concrete rewrites: static typing (examples with Crystal and an Idris‑style dependent types sketch, plus RubyVM::InstructionSequence… | ||
| Infinite State Machine Poetry in, with, and by Clojure | Clojure/conj 2017 | 2017-10-12 |
Clojure code generates poems using a Markov chain on Keats (≈2,000 lines, ~13,660 words, ~80k chars) and a recurrent neural network on Shakespeare (≈125k… | ||
| Do Androids Dream of Electronic Dance Music? | RubyKaigi 2017 | 2017-09-18 |
A pipeline converts 110 MIDI files (royalty-free deadmau5 samples) into TFRecords and trains an LSTM via TensorFlow and Magenta (mostly Python with ~5% Ruby… | ||
| Machine Learning with Elixir and Phoenix | ElixirConf EU 2017 | 2017-05-04 |
Claims a homegrown Elixir neural network can predict 20‑day returns on S&P 500 (SPY) data and be deployed in a Phoenix app. Uses Python to prep data, then… | ||
| Dōmo arigatō, Mr. Roboto: Machine Learning with Ruby | RubyConf 2016 | 2016-11-10 |
A Ruby implementation trains a neural network on the MNIST dataset using the RubyFann gem and serves a React front end with a Sinatra backend; the model maps… | ||
| Machine Learning with Clojure and Apache Spark | EuroClojure 2016 | 2016-10-25 |
Compares Clojure bindings for Spark by building a binary classifier on 600,000 LA police stops using flambo vs sparkling, trains a decision tree (max depth 5… | ||
| Booting Up: Hiring and Growing Boot Camp Graduates | RailsConf 2016 | 2016-05-04 |
States the concrete claim: in 2015 nearly a hundred programming boot camps produce thousands of graduates, and hiring needs change accordingly. Describes which… | ||
| The Hitchhiker's Guide to Ruby GC | RubyConf 2015 | 2015-11-15 |
Shows that garbage collection, not just databases or algorithms, is the real culprit: a Sinatra app hits about half a million live objects on boot, Ruby 1.9.3… | ||
| So Long, Hoboken: Migrating a Huge Production Codebase from Sinatra to Rails | RailsConf 2015 | 2015-04-21 |
A migration moves a 12–14 small-app Sinatra suite into Rails by choosing between melting/mounting (Rails boots Sinatra, hurting memory and reload performance)… | ||
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