seed ( seed = 42 ) # loop over shingle frequency database (`db`) db2 = Counter () for original in db. I work with people of very different backgrounds, from all over the world, and they. We believe the most interesting research questions are derived from real world problems. prod ( for cfg in settings ])) # Count factor for original shingle n_factor_original = int (( n_augm_rounds / pct_augmented ) * ( 1 - pct_augmented )) # reproducibility np. At Facebook, research permeates everything we do. the total count will be 10-1000x larger) n_augm_rounds = 10 # maximum percentage of augmentions pct_augmented = 0.1 pct_augmented *= ( 1.0 + np. import augtxt.keyboard_layouts as kbl from gmenters import wordaug import numpy as np from collections import Counter # Augmentation settings: Probability of typological errors settings = # Number of augmentation rounds (i.e.
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Laymen’s text might not include each possible edge case. 'Facebook shuts down robots after they invent their own language,' Londons Telegraph. High quality corpora try to avoid such errors, and corpora based But in the past week or so, some media outlets have published reports on the work that are alarmist in tone. If you search for a more advanced croping plugin, there are some. A typical usecase would be to crop rectangular images into squares. It allows to crop the image only in one dimension (no zooming). It aims to be minimalistic and very easy to use for the end-user. Use text augmentation to produce possible edge case of errornous text. A jQuery plugin for croping images by dragging, inspired by Facebook cover photo. In order to increase the generalizibility of a trained ML model, we can Įxtra: Augment text by adding typological errors shrink_k_backwards ( encoded, unkid ) # Step 2: Shingle sequences again shingled = encoded = encode_with_vocab ( shingled, VOCAB, unkid ) #. encode_with_vocab ( shingled, VOCAB, unkid ) # Identify k's that are actually used klist = ks. upsert_word_to_vocab ( VOCAB, "" ) encoded = ks. identify_vocab ( shingled, n_max_vocab = 10 ) VOCAB, unkid = ks.
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import kshingle as ks data = # Step 1: Build a VOCAB shingled = VOCAB = ks. Sequences that contain at least one encoded shingle across all examples.
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Theįunction ks.shrink_k_backwards identifies k values that generate Generated sequences only contains encoded elements. And less frequent shingles might be excluded in
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It helps managers get the full overview of their operation, to understand better, plan, optimise and improve the movement of people and traffic in and around an event.For bigger k values, the generate longer shingles that occur lessįrequent. Fortunately, advances in crowd-management technologies mean that event organisers can now make better decisions, based on accurate, real-time information gathered from on-the-ground live measurements and data analysis solutions. Historically, this kind of management has been a combination of sifting through masses of historical data manually and making educated guesses and predictions. Whether it’s a sporting event, a festival, or a concert, organisers must keep the attendee’s journey on track and keep the vehicle and foot traffic flowing smoothly to, from, and around the venue, to ensure the best possible safety. epithelial damage, reduce mucin expression and increase baseline smooth mus. While there are hundreds of options available, there’s really only a handful being used by top technical teams. Imagine a scenario where the press of bodies leads to risks of physical safety, or where the sudden influx of people causes miles of traffic congestion around the event. associations with emergency department visits for cardiac conditions. Choosing a project management tool shouldn’t feel like you’re reinventing the wheel. Endoplasmic Reticulum (Rough & Smooth) -Folded membranes that act like a road in the cell, transporting substances such as proteins. Managing crowd safety is of paramount importance.