fkdosilovic

NLP Tutorials and Workshops

• Beyond Paragraphs: NLP for Long Sequences - Overview | Resources | Lecture
• Event-Centric Natural Language Processing - Overview | Resources | Lecture
• Towards Reproducible Machine Learning Research in NLP - Overview | Resources | Lecture
• Zero- and Few-Shot NLP with Pretrained Language Models - Overview | Resources | Lecture

99991

import subprocess, getpass

def get_gpu_usage():
    """
    Returns a dict which contains information about memory usage for each GPU.

    In the following output, the GPU with id "0" uses 5774 MB of 16280 MB.
    253 MB are used by other users, which means that we are using 5774 - 253 MB.

    {

llimllib

Richard W. Hamming

January 1969

One Man's View of Computer Science

Abstract

A number of observations and comments are directed toward suggesting that more than the usual engineering flavor be given to computer science. The engineering

ferrine

import torch.nn
import collections

class Builder(object):
    def __init__(self, *namespaces):
        self._namespace = collections.ChainMap(*namespaces)

    def __call__(self, name, *args, **kwargs):
        try:
            return self._namespace[name](*args, **kwargs)

tux-00

import configparser
from dataclasses import dataclass


@dataclass
class Sections:
    raw_sections: dict

    def __post_init__(self):
        for section_key, section_value in self.raw_sections.items():

HarshTrivedi

import torch
from torch import LongTensor
from torch.nn import Embedding, LSTM
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence

## We want to run LSTM on a batch of 3 character sequences ['long_str', 'tiny', 'medium']
#
#     Step 1: Construct Vocabulary
#     Step 2: Load indexed data (list of instances, where each instance is list of character indices)

mivade

"""This is free and unencumbered software released into the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.

In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

bishboria

These links no longer work. Springer have pulled the free plug.

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

dannguyen

Using youtube-dl and gifify from the command-line

Turn this cute YouTube cat video into a briefer-but-still-cute GIF:

Software to download

• youtube-dl is a command-line tool for quickly downloading video files from a given YouTube URL