Author Archives: lhmay

Categorizing Listing Photos at Airbnb

https://medium.com/airbnb-engineering/categorizing-listing-photos-at-airbnb-f9483f3ab7e3 Large-scale deep learning models are changing the way we think about images of homes on our platform. Authors: Shijing Yao, Qiang Zhu, Phillippe Siclait Airbnb is a marketplace featuring millions of homes. Travelers around the world search on the platform and discover the best homes for their trips. Aside from location and price, listing photos […]

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Compliance bias in mobile experiments

From unofficial Google data science blog by DANIEL PERCIVALhttp://www.unofficialgoogledatascience.com/2018/03/quicker-decisions-in-imperfect-mobile.html Randomized experiments are invaluable in making product decisions, including on mobile apps. But what if users don’t immediately uptake the new experimental version? What if their uptake rate is not uniform? We’d like to be able to make decisions without having to wait for the long […]

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Big data:Hadoop vs. Spark

  Big data is data sets that are so voluminous and complex that traditional data-processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. To understand the phenomenon that is big data, it is often described using five Vs: Volume, Velocity, Variety, Veracity and Value Volume refers to the vast amounts of […]

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Simpson’s Paradox

Simpson’s paradox for quantitative data: a positive trend ( blue line and red line  ) appears for two separate groups, whereas a negative trend (dotted line) appears when the groups are combined. Simpson’s paradox, or the Yule–Simpson effect, is a phenomenon in probability and statistics, in which a trend appears in several different groups of data but disappears or reverses […]

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Experimentation Key Steps

  Within webpages, nearly every element can be changed for a split test. Marketers and web developers may try testing: Visual elements: pictures, videos, and colors Text: headlines, calls to action, and descriptions Layout: arrangement and size of buttons, menus, and forms Visitor flow: how a website user gets from point A to B Some […]

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Attribution modeling

An attribution model is the rule, or set of rules, that determines how credit for sales and conversions is assigned to touchpoints in conversion paths. For example, the Last Interaction model in Analytics assigns 100% credit to the final touchpoints (i.e., clicks) that immediately precede sales or conversions. In contrast, the First Interaction model assigns 100% credit to touchpoints that initiate conversion […]

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Online lender Kabbage to launch payment services by year-end

NEW YORK (Reuters) – Kabbage Inc, a U.S. online lender for small businesses, plans to launch payment processing services by year-end, President Kathryn Petralia said on Monday, helping it to diversify and compete more directly with industry leaders PayPal Holdings Inc (PYPL.O) and Square Inc (SQ.N). The Atlanta-based startup will offer tools to enable clients, […]

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Comparing Performance of 6 Classification Models

In the example below 6 different algorithms are compared: Logistic Regression Linear Discriminant Analysis K-Nearest Neighbors Classification and Regression Trees Naive Bayes Support Vector Machines # Python Code # Compare Algorithms import pandas import matplotlib.pyplot as plt from sklearn import model_selection from sklearn.linear_model import LogisticRegression from sklearn.tree import DecisionTreeClassifier from sklearn.neighbors import KNeighborsClassifier from sklearn.discriminant_analysis […]

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Gradient Descent

Gradient descent is an optimization algorithm used to minimize some function by iteratively moving in the direction of steepest descent as defined by the negative of the gradient. In machine learning, we use gradient descent to update the parameters of our model. Parameters refer to coefficients in Linear Regression and weights in neural networks. Learning rate The size of these steps […]

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Customer Engagement Dashboard

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