- Taehoon Kim deep learning resources https://github.com/carpedm20/deep-learning-study
- Denny Britz deep learning paper notes https://github.com/dennybritz/deeplearning-papernotes/tree/master/notes
- deep learning for nlp links https://github.com/andrewt3000/DL4NLP/blob/master/README.md
- https://github.com/keonkim/awesome-nlp#name-entity-recognition
- (old) stanford nlp resources http://www-nlp.stanford.edu/links/statnlp.html
- 2013 NAACL deep learning in nlp http://nlp.stanford.edu/courses/NAACL2013/
- NMT implementations https://github.com/jonsafari/nmt-list
- What I learned from Deep learning summer school 2016 https://www.linkedin.com/pulse/what-i-learned-from-deep-learning-summer-school-2016-hamid-palangi
- NLP tools http://www.phontron.com/nlptools.php
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const std = @import("std"); | |
const assert = std.debug.assert; | |
/// An intrusive heap implementation backed by a pairing heap[1] implementation. | |
/// | |
/// Why? Intrusive data structures require the element type to hold the metadata | |
/// required for the structure, rather than an additional container structure. | |
/// There are numerous pros/cons that are documented well by Boost[2]. For Zig, | |
/// I think the primary benefits are making data structures allocation free | |
/// (rather, shifting allocation up to the consumer which can choose how they |
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#! /usr/bin/env python3 | |
import sys | |
from bst import * | |
from collections import defaultdict as dd | |
def paths_with_sum_helper(node, running_sum, seen_sums, target_sum): | |
if not node: return 0 | |
running_sum += node.val |
Sorry, this is too big to display.
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"""A simple implementation of a greedy transition-based parser. Released under BSD license.""" | |
from os import path | |
import os | |
import sys | |
from collections import defaultdict | |
import random | |
import time | |
import pickle | |
SHIFT = 0; RIGHT = 1; LEFT = 2; |
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Compression for serving | |
To Index or not to Index: Time-Space Trade-Offs in Search Engines with Positional Ranking Functions | |
On Inverted Index Compression for Search Engine Efficiency | |
Model management | |
Laser | |
http://dl.acm.org/citation.cfm?id=2556252&dl=ACM&coll=DL&CFID=769147842&CFTOKEN=71514156 | |
AirBnb Aerosolve |
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Write a program that does what it’s supposed to do | |
Write idiomatic code | |
Debug a program that you wrote | |
Debug a program someone else wrote | |
Debug the interaction between a system you wrote and one you didn’t | |
File a good bug report | |
Modify a program you didn’t write | |
Test a program you wrote | |
Test a program you didn’t write | |
Learn a new programming language |
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mysqladmin5 extended-status -uroot -i 1 -r | grep "InnoDB_rows_read" | |
# or other stat |
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import itertools as it | |
def flatten(listOfLists): | |
return list(it.chain.from_iterable(listOfLists)) | |
def all_subsets(xs): | |
try: iter(xs) | |
except TypeError: return [] | |
return flatten([it.combinations(xs, i) for i in range(len(xs)+1)]) |
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