2-day longest streak
Hi there 👋 <!-- jbowles/jbowles is a ✨ _special_ ✨ repository because its README.md (this file) appears on your GitHub profile. Here are some ideas to get you started: 🔭…
Hi there 👋
<!--
jbowles/jbowles is a ✨ _special_ ✨ repository because its README.md (this file) appears on your GitHub profile.
Here are some ideas to get you started:
- 🔭 I’m currently working on ...
- 🌱 I’m currently learning ...
- 👯 I’m looking to collaborate on ...
- 🤔 I’m looking for help with ...
- 💬 Ask me about ...
- 📫 How to reach me: ...
- 😄 Pronouns: ...
- ⚡ Fun fact: ...
Joshua Bowles
Myself
1. I'm a talker. * I often get excited and loud -- I'm not angry, I'm very rarely upset. * It's okay to tell me I'm talking too much. * I take notes, which means I’m looking down, but I am listening to you. 2. If I'm upset I tell people directly. 3. I'm a linguist by training (and computational linguistics). I didn't study computer science. * I see myself as having acquired skill through lots of hard work. 3. I'm an academic at heart: more of a “fox” than a “mole” (ask me about it). 4. I'm not good at small talk, I get nervous at parties or when meeting new people. 5. I've had a few different careers and worked in some very remote places. I have known and interacted with a broad and diverse number of people. I'm happy to meet more. 6. I want to see other people succeed. I want you to succeed. Your success is my success. * My goal is to help you multiply your strengths while pushing you out of your comfort zone. * Each person is different, my management style may shift depending on your strengths and areas of growth. 7. I've done AI and ML before it was cool, it's not magic, it's a lot of (janitorial) work; I like janitor work. * AI is infrastructure * The biggest challenges for AI and data are not engineering, but product-market fit.My Role
My role is to support and develop world-class engineers, then get out of the way. That's it. Everything else follows.My Sense of Management
Management is mostly common sense and caring about people, products, and customers.- I expect
high functioningindividuals, which means that you're proactive about collaborating with teams and services that you may impact or interact with. - I expect you to find a way around blockers (world-class people are rarely ever "blocked").
- I expect you to learn what you need.
- I expect a general awareness that we're all in this together (whatever _it_ is).
- I hold monthly performance observations.
- I hold weekly one-on-one meetings, focusing on feedback for both of us.
Scope
Teams are incubators to develop world-class engineers through focusing on professional development goals and aligning those goals as best we can with specific projects. We solve fundamental problems by focusing on standards and best practices, innovating where needed. We seek to be a resource to others through example, communication, coordination, and collaboration.Vision
Develop world-class engineers. That's it. Everything else follows.- Make it work, make it right, make it fast.
- Work the problem, step by step.
- Focus on fundamentals.
- Engineering is also about intuition.
- Trust _and_ Verify.
- Arrogance is ignorance.
- Lead by example.
- Stable is predictable, predictable is scalable.
- Iteration fosters adaptability, adaptability leads to evolution.
- Marginal gains add up.
- Too much planning is procrastinating.
- If you can't measure it, you don't understand it.
A Note on Skill and Talent
Talent is capacity, skill is praxis (putting practice into application). You don't need talent to become a highly skilled person, but you might need to invest a lot more time. On the other hand, talent won't get you anywhere unless you put in the effort. Talent is a false equivalence with skill, nor does it equate with interest or passion.-
nlpt
Natural Language Processing Toolkit written in Go (DEPRECATED see individual packages prefixed nlpt-)
Go ★ 34 10y agoExplain → -
artifact
Artifiact is a collection of code relevant to general Artificial Intelligence in Clojure
Clojure ★ 6 14y agoExplain → -
nlpt-cld2
Go wrapper for the cld2 C++ project from google chrome tools
C++ ★ 6 7y agoExplain → -
disfun
Distance Functions including ngram and levenshtein, haversine, euclidean, etc...
Go ★ 5 9y agoExplain → -
siw
Simple stats for counting words from files or websites
Go ★ 3 12y agoExplain → -
elixirnlpt
Natural Language Processing Toolkit for Elixir
Elixir ★ 2 11y agoExplain → -
wordvec
go implementation of word2vec algorithms with web server and api (IN PROGRESS)
Go ★ 2 10y agoExplain → -
te_rex
simple nlp tools for small data sets
Ruby ★ 1 10y agoExplain → -
smallgear
Experiment API for natural language processing
Go ★ 1 11y agoExplain → -
lexer ⑂
GO API To Help You Create Hand-Written Lexers - See original author's post 'go_parser' Project for the Parser API and 'go_lexer_matcher' Project for a Fluent Interface for Matching Tokens.
Go ★ 1 10y agoExplain → -
nlpt-detect
natural language detection using cld2 go wrapper
Go ★ 1 10y agoExplain → -
nlpt-ir
basic information retrieval stuff, specifically tfidf
Go ★ 1 10y agoExplain → -
wordlab
pre-processes and formats words, specifically for use in classification or clustering algorithms (knn, k-means, x-means, etc...)
Go ★ 1 10y agoExplain → -
nlpt-tkz
natural language tokenization using various types of tokenizer, including a state function lexer, unicode matcher, and basic white space splitter
Go ★ 1 10y agoExplain → -
topiclab
topic modeling, text categorization
Go ★ 1 11y agoExplain → -
hsp
toying with go-kit
Go ★ 1 10y agoExplain → -
money
a money type in go with operations and formatting
Go ★ 1 10y agoExplain → -
clojure-learning
learn me some clojure
Clojure ★ 1 13y agoExplain → -
entropy
machine learning applied to production logs
Clojure ★ 1 14y agoExplain → -
signals_and_noise_selectionns
PDF formatted selections from my novel Signals and Noise
★ 0 3d agoExplain → -
ltx
All my LaTeX documents
TeX ★ 0 17d agoExplain → -
fastrtc ⑂
The python library for real-time communication
★ 0 1y agoExplain → -
dental-embeddings
No description.
★ 0 1y agoExplain → -
TEXTOIR ⑂
TEXTOIR is the first opensource toolkit for text open intent recognition. (ACL 2021)
★ 0 2y agoExplain → -
jbowles
No description.
★ 0 1y agoExplain → -
pyo3 ⑂
Rust bindings for the Python interpreter
★ 0 3y agoExplain → -
rustling-ontology ⑂
Ontology for rustling
Rust ★ 0 7y agoExplain → -
rustling ⑂
Rust implementation of Duckling
Rust ★ 0 8y agoExplain → -
rocinante
Experiments with serving NLP models in rust
Rust ★ 0 6y agoExplain → -
algos_math_comp
Classic math or computer science algorithms implemented for learning in Rust, Julia, Go, C++
Rust ★ 0 2mo agoExplain → -
thinkstatsgo
go code for Think Stats by Allen B. Downey
Go ★ 0 6y agoExplain → -
rust-bert ⑂
Rust native DistilBERT implementation
Rust ★ 0 6y agoExplain → -
rust-tokenizers ⑂
Rust-tokenizer is a drop-in replacement for the tokenization methods from the Transformers library
★ 0 6y agoExplain → -
ThinkStats2 ⑂
Text and supporting code for Think Stats, 2nd Edition
Jupyter Notebook ★ 0 6y agoExplain → -
PRML ⑂
PRML algorithms implemented in Python
★ 0 6y agoExplain → -
match_zoo_examples_and_tutorials
Examples and tutorials for the match zoo project: https://github.com/NTMC-Community/MatchZoo
Jupyter Notebook ★ 0 6y agoExplain → -
MatchZoo ⑂
Facilitating the design, comparison and sharing of deep text matching models.
★ 0 6y agoExplain → -
MatchZoo-py ⑂
Facilitating the design, comparison and sharing of deep text matching models.
★ 0 6y agoExplain → -
mock_skills_gen
tutorial with a generated data set of student assessment skills
Python ★ 0 6y agoExplain → -
mml-book.github.io ⑂
Companion webpage to the book "Mathematics For Machine Learning"
★ 0 6y agoExplain → -
StatsWithJuliaBook ⑂
No description.
★ 0 6y agoExplain → -
deeplearning-models ⑂
A collection of various deep learning architectures, models, and tips
★ 0 6y agoExplain → -
gorgonia ⑂
Gorgonia is a library that helps facilitate machine learning in Go.
★ 0 6y agoExplain → -
goldberg_unreason_effective_char_level_lm
julia and rust versions of goldberg's blog post
Jupyter Notebook ★ 0 6y agoExplain → -
vtext ⑂
NLP in Rust with Python bindings
Rust ★ 0 6y agoExplain → -
sbrweb ⑂
Sabre Web Services
★ 0 7y agoExplain → -
string_dist ⑂
String distances in rust
★ 0 7y agoExplain → -
NGrams.jl ⑂
No description.
Julia ★ 0 7y agoExplain → -
GenderInference.jl ⑂
Tools for inferring gender from first names
Julia ★ 0 7y agoExplain → -
hmmm ⑂
Hidden Markov Models in Rust
Rust ★ 0 7y agoExplain → -
tch-rs ⑂
Rust bindings for PyTorch
Rust ★ 0 7y agoExplain → -
courier ⑂
A fast, GoLang message receiver and sender for SMS and IP channels
Go ★ 0 7y agoExplain → -
snips-nlu-rs ⑂
Snips NLU rust implementation
Rust ★ 0 7y agoExplain → -
citar ⑂
Citar HMM part-of-speech tagger
Go ★ 0 7y agoExplain → -
fmr ⑂
Functional Meaning Representation and Semantic Parsing Framework
Go ★ 0 7y agoExplain → -
gsdmm-rust ⑂
GSDMM: Short text clustering (Rust implementation)
Rust ★ 0 9y agoExplain → -
VMLS.jl ⑂
No description.
Julia ★ 0 7y agoExplain → -
word2vec-rs ⑂
pure rust implemention of word2vec
Rust ★ 0 9y agoExplain → -
tvm-rust ⑂
Rust bindings for TVM runtime
Rust ★ 0 7y agoExplain → -
JuML.jl ⑂
Machine Learning in Julia
Julia ★ 0 7y agoExplain → -
whatlang-rs ⑂
Natural language detection library for Rust
Rust ★ 0 7y agoExplain → -
snips-nlu-ontology ⑂
Ontology of Snips NLU
Rust ★ 0 7y agoExplain → -
main ⑂
Framework to streamline use of neural networks
Python ★ 0 7y agoExplain → -
math_soup
Experimenting and learning rust with computational math
Rust ★ 0 7y agoExplain → -
rust ⑂
Rust language bindings for TensorFlow
Rust ★ 0 7y agoExplain → -
wyrm ⑂
Autodifferentiation package in Rust.
Rust ★ 0 7y agoExplain → -
juice ⑂
The Hacker's Machine Learning Engine (formerly known as leaf)
Rust ★ 0 7y agoExplain → -
CFG ⑂
Generator for phrases based on context-free grammars
Rust ★ 0 8y agoExplain → -
rustlearn ⑂
Machine learning crate for Rust
Rust ★ 0 7y agoExplain → -
Flux.jl ⑂
Relax! Flux is the ML library that doesn't make you tensor
Julia ★ 0 7y agoExplain → -
rs-natural ⑂
Natural Language Processing for Rust
Rust ★ 0 8y agoExplain → -
luhn-rs
luhn algorithm in rust
Rust ★ 0 7y agoExplain → -
cld2 ⑂
CLD2 (Compact Language Detector 2) bindings for Go (golang)
C++ ★ 0 7y agoExplain → -
Text.jl ⑂
Numerous tools for text processing
Julia ★ 0 9y agoExplain → -
GirApp
giraffe F# web app sample for play and learn
F# ★ 0 8y agoExplain → -
learn_fsharp
fsharp learning
F# ★ 0 8y agoExplain → -
libpostal-rest-docker ⑂
Run libpostal inside a docker container
Shell ★ 0 9y agoExplain → -
gopostal ⑂
Go (cgo) interface to libpostal for fast international address parsing/normalization
Go ★ 0 9y agoExplain → -
goml ⑂
On-line Machine Learning in Go (and so much more)
Go ★ 0 9y agoExplain → -
pachyderm ⑂
Containerized Data Analytics
Go ★ 0 10y agoExplain → -
tensorflow ⑂
Computation using data flow graphs for scalable machine learning
C++ ★ 0 10y agoExplain → -
matchr ⑂
An approximate string matching library for the Go programming language.
Go ★ 0 10y agoExplain → -
go-freeling ⑂
Golang Natural Language Processing
Go ★ 0 10y agoExplain → -
i18n ⑂
golang package for basic i18n features, including message translation and number formatting
Go ★ 0 11y agoExplain → -
word2vec
Automatically exported from code.google.com/p/word2vec
C ★ 0 10y agoExplain → -
gohll ⑂
An implementation of HLL++ in go
Go ★ 0 10y agoExplain → -
learn-elixir
learning elixir
Elixir ★ 0 11y agoExplain → -
DeepLearning ⑂
Deep Learning (Python, C/C++, Java, Scala, Go)
C ★ 0 11y agoExplain → -
go-neural ⑂
Neural network implementation on golang
Go ★ 0 12y agoExplain → -
RF.go ⑂
Random Forest implemtation in GoLang
Go ★ 0 12y agoExplain → -
countries ⑂
World countries in JSON, CSV and XML. Any help is welcome!
★ 0 12y agoExplain → -
han ⑂
Hypermedia API Navigation spec
★ 0 12y agoExplain → -
texmf
Local customized packages, image files, bibliographies, etc., for compiling LaTeX
Emacs Lisp ★ 0 8y agoExplain → -
simpletransport ⑂
No description.
Go ★ 0 13y agoExplain →
No repos match these filters.