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Recommendations The journey to build an explainable AI-driven recommendation system to help scale sales efficiency across LinkedIn Authored byJilei Yang Staff Software Engineer, Machine Learning at LinkedIn | PhD in Statistics April 6, 2022 Co-authors: Jilei Yang, Parvez Ahammmad, Fangfang Tan, Rodrigo Aramayo, Suvendu Jena, Jessica Li At LinkedIn, we have the opportunity to work with many differe
Co-authors: Keqiu Hu, Jonathan Hung, Haibo Chen, and Sriram Rao At LinkedIn, we use Hadoop as our backbone for big data analytics and machine learning. With an exponentially growing data volume, and the company heavily investing in machine learning and data science, we have been doubling our cluster size year over year to match the compute workload growth. Our largest cluster now has ~10,000 nodes
Dear Colleagues, The recent announcement that the United States Trade Representative will discuss options to waive some COVID-19 vaccine intellectual property (IP) rights has created some confusion to the world. Has Pfizer done enough to ensure fair and equitable distribution of our COVID-19 vaccine? Is the proposed waiver going to bring solutions or create more problems? I am writing to you today
Co-authors: Xiang Zhang and Jingyu Zhu Introduction The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods. But it also has some drawbacks, such as complexity and additional development/operational overheads. One of our features for Premium members on
Site up and secure is a fundamental element of how we operate, and site reliability engineers (SREs) play a critical role in fulfilling that responsibility. Talent has always been the number one operating priority, and over the last few years, we’ve been running multiple programs to identify, hire, and develop talented SREs, including those without an SRE background. On this journey, we made a few
There is more and more speculation in the press on how the industry will navigate the death of the cookie. However, we see a much larger and more nuanced fundamental change coming which could use more press coverage: the rapid deceleration of 3rd party deterministic ID marketplaces. If you’re well-versed in digital marketing measurement you know that the disappearing cookie isn’t wholly the proble
Open Source Open sourcing Kube2Hadoop: Secure access to HDFS from Kubernetes Co-authors: Cong Gu, Abin Shahab, Chen Qiang, and Keqiu Hu Editor's note: This blog has been updated. LinkedIn AI has been traditionally Hadoop/YARN based, and we operate one of the world’s largest Hadoop data lakes, with over 4,500 users and 500PB of data. In the last few years, Kubernetes has also become very popular at
TL;DR Named functions are useful for a good debugging experience, while anonymous functions provides context scoping for easier development. Arrow functions should only be used when functions act as data. Functions are fun! They are literally one of the most used programming terms along with loops, variables, and mathematical operations. However we do not nearly have enough knowledge about the ins
I’m going to go out on a limb here and make a prediction. Since the web’s inception, much of our industry has spent effort to be on the web but to escape web technologies like JavaScript, HTML and CSS. Examples include Java Applets (1995–around 2013), Microsoft ActiveX (shipped with Internet Explorer 3.0 in 1996), Microsoft’s ASP.NET Web Forms (2002), JavaServer Faces (JSF), the Google Web Toolkit
Agree & Join LinkedIn By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. こんにちは、マイクロソフトの石井 哲平です。 2007年に新卒でマイクロソフトのサポートエンジニアとして入社をし、長らくエンジニアを楽しんで来ました。2018 年より、サポートエンジニアのチームでマネージャー職をしています。 サポートエンジニアという職業に魅力を感じ、都度サポートエンジニアであることを選び続けてきたという自負はありますが、あらためて、マネージャーという職について、その価値の言語化が必要だと感じた次第です。 サポートエンジニアって何？という方に知ってもらいたい。 あるいは、今サポートエンジニアだよという方
Open Source How LinkedIn customizes Apache Kafka for 7 trillion messages per day Co-authors: Jon Lee and Wesley Wu Apache Kafka is a core part of our infrastructure at LinkedIn. It was originally developed in-house as a stream processing platform and was subsequently open sourced, with a large external adoption rate today. While many other companies and projects leverage Kafka, few—if any—do so at
Recommendations The AI Behind LinkedIn Recruiter search and recommendation systems Co-authors: Qi Guo, Sahin Cem Geyik, Cagri Ozcaglar, Ketan Thakkar, Nadeem Anjum, and Krishnaram Kenthapadi LinkedIn Talent Solutions serves as a marketplace for employers to reach out to potential candidates and for job seekers to find career opportunities. A key mechanism to help achieve these goals is the LinkedI
Authored byMars Lan Co-Founder & CTO at Metaphor | Co-creator of DataHub August 14, 2019 Co-authors: Mars Lan, Seyi Adebajo, Shirshanka Das Editor’s note: Since publishing this blog post, the team open sourced DataHub in February 2020. You can read more on the journey of open sourcing the platform here. As the operator of the world’s largest professional network and the Economic Graph, LinkedIn’s
Authored byMohak Shroff Senior Vice President of Engineering at LinkedIn July 23, 2019 The pursuit of our mission to connect the world’s professionals to make them more productive and successful is deeply dependent on the technology and infrastructure we build and maintain. Ten years ago, we had 50 million members. Fast forward five years and that number jumped to 300 million. Today, we have more
The answer to do hard work without effort is automation. So I created a bot that does all the tedious work while I sit back doing nothing. I am a guy that likes to learn new stuff, so for some time now I wanted to find out if all the fuss about Machine Learning (ML) was worth it. At university I learned a lot about Machine Learning and Artificial Intelligence but unfortunately I've never had the c
Vladimír Gorej Senior Open Source Software Engineer at SmartBear (PSD I, PSM I, GCP) The Page Object pattern is certainly the most utilized pattern when it comes to web application test automation. It is a powerful method for reducing code maintenance costs and code duplication which leads to increase of the re-usability and robustness. All this benefits become apparent when you're testing complex
Barry Overeem Co-founder The Liberators & Columinity: I create content & products and facilitate (Liberating Structures) workshops to unleash (Agile & Scrum) teams all over the world! According to the Scrum Guide, the Scrum Master is responsible for ensuring Scrum is understood and enacted. Scrum Masters do this by ensuring that the Scrum Team adheres to Scrum theory, practices, and rules. The Scr
Blended learning is all about the students: combining instruction with digital resources to help increase student achievement and engagement. In this course, Chris Mattia explores the various aspects of blended learning, and provides guidelines to create a blended classroom that meets students' diverse learning needs. The techniques rely on technologies such as Google Apps, Android and iOS devices
Agree & Join LinkedIn By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
By the second semester of my freshman year at Harvard, I had started going to classes I wasn’t signed up for, and had pretty much stopped going to any of the classes I was signed up for – except for an introduction to economics class called “Ec 10.” I was fascinated by the subject, and the professor was excellent. One of the first things he taught us was the supply and demand diagram. At the time
Beginners to artificial neural networks (ANNs) are likely to ask some questions. Some of these questions include what is the number of hidden layers to use? How many hidden neurons in each hidden layer? What is the purpose of using hidden layers/neurons? Is increasing the number of hidden layers/neurons always gives better results? I am pleased to tell we could answer such questions. To be clear,
One of the fun things about being a leader at a hyper-growth company is that you don’t just have the opportunity to change things — you must drive change to keep up. And working in the new and rapidly evolving field of Data Science (DS) entails another level of rapid change. We are evolving within the company and as an industry in parallel. At Airbnb, we think of data as the voice of our users at
Hello everyone! Microsoft Build is upon us once again. It’s my favorite time of year because it’s so exciting to introduce our developer community to the newest tools that will empower them to accelerate the world’s digital transformation and create the future. During Satya Nadella’s Build keynote, he introduced the world to one such tool that may sound a little familiar: Project Kinect for Azure.
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