Our Favorite Posts Of Last Week (Apr 22, 2018)

URLs, Crawling, and PageRank; Fundamentals of SEO

Those who know me will not be surprised to hear I have a lot of pet peeves; I’m easily annoyed. One of those pet peeves is URLs. Specifically, about the lack of respect that URLs are accorded by developers and marketers alike.
Link: http://www.stateofdigital.com/urls-crawling-pagerank-fundamentals/
Word Count: 3336

Raleigh SEO Meetup - Paul Shapiro - Technical SEO

Upcoming SlideShare Loading in …5 × Raleigh SEO Meetup - Paul Shapiro - Technical SEO 1. Paul Shapiro | @fighto Beyond The Makeup Technical SEO 2. Paul Shapiro | @fighto 3. Paul Shapiro | @fighto Raleigh Source: http://www.waymarking.com/gallery/image.
Link: https://www.slideshare.net/paulshapiro/raleigh-seo-meetup-paul-shapiro-technical-seo
Word Count: 1197

Why product market-fit is so important for Growth Marketing12 min read

One year after launching, UBER’s growth was so strong that it got one new rider for every 7 rides – without spending a single dollar on marketing. [5] Instagram had 25,000 signups on its first day. [6]
Link: https://www.kevin-indig.com/why-product-market-fit-is-so-important-for-growth-marketing/
Word Count: 2184

Compositional clustering in task structure learning

Humans are remarkably adept at generalizing knowledge between experiences in a way that can be difficult for computers. Often, this entails generalizing constituent pieces of experiences that do not fully overlap, but nonetheless share useful similarities with, previously acquired knowledge.
Link: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006116
Word Count: 10869

A Must-Read Introduction to Sequence Modelling (with use cases)

Artificial Neural Networks (ANN) were supposed to replicate the architecture of the human brain, yet till about a decade ago, the only common feature between ANN and our brain was the nomenclature of their entities (for instance – neuron).
Link: https://www.analyticsvidhya.com/blog/2018/04/sequence-modelling-an-introduction-with-practical-use-cases/
Word Count: 1752

How we serve 25M API calls from 10 scalable global endpoints for $150 a month

Our users typically call our API on each page request on their websites to geolocate their users and localize their content. So this particular failure was directly impacting our users’ websites on the biggest sales day of the year.
Link: https://medium.freecodecamp.org/how-we-serve-25m-api-calls-from-10-scalable-global-endpoints-for-150-a-month-911002703280
Word Count: 1307

NLP –  Building a Question Answering Model

I recently completed a course on NLP through Deep Learning (CS224N) at Stanford and loved the experience. Learnt a whole bunch of new things. For my final project I worked on a question answering model built on Stanford Question Answering Dataset (SQuAD).
Link: https://www.kdnuggets.com/2018/04/nlp-question-answering-model.html
Word Count: 1331

An introduction to HTTP/2 & Service Workers for SEOs

Upcoming SlideShare Loading in …5 × An introduction to HTTP/2 & Service Workers for SEOs 1. An introduction to HTTP/2 & Service Workers for SEOs @TomAnthonySEO 2. EMAILS RUNNING OUT OF POWER 3.
Link: https://www.slideshare.net/TomAnthony/an-introduction-to-http2-service-workers-for-seos
Word Count: 1605

Building a FAQ Chatbot in Python – The Future of Information Searching

What do we do when we need any information? Simple: “We Ask, and Google Tells”. But if the answer depends on multiple variables, then the existing Ask-Tell model tends to sputter. State of the art search engines usually cannot handle such requests.
Link: https://www.analyticsvidhya.com/blog/2018/01/faq-chatbots-the-future-of-information-searching/
Word Count: 1666

Hyper Text Coffee Pot Control Protocol

The Hyper Text Coffee Pot Control Protocol (HTCPCP) is a facetious communications protocol for controlling, monitoring, and diagnosing coffee pots. It is specified in RFC 2324, published on 1 April 1998 as an April Fools' Day RFC,[2] as part of an April Fools prank.
Link: https://en.wikipedia.org/wiki/Hyper_Text_Coffee_Pot_Control_Protocol
Word Count: 483