Klaviyo công khai
[search 0]
Thêm

Download the App!

show episodes
 
Loading …
show series
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Anomaly Detection It’s our third November on the Klaviyo Data Science Podcast, and if you work in ecommerce, you know that November means one thing: Black Friday and (usually) Cyber Monday, i.e. the month of the year where everything changes. Traditionally, we’ve talked a…
 
I’ll let you in on a secret: this podcast does not cover everything. We cover a wide array of projects, go into detail on a variety of aspects of them, and speak to a diverse panel of data scientists and people related to the data science world, but we still can’t cover everything. This month, to give you a taste of what we haven’t been able to sho…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Using NLP to communicate at scale Last episode, we discussed the history and practice of natural language processing, or NLP. This month, we’re here to discuss an exciting and cutting-edge application: using NLP to help businesses converse with their customers at scale. S…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… What’s the deal with natural language? Natural language processing, or NLP, is one of the dominant forces in modern data science, and it’s produced a host of data science-powered products many people take for granted as a basic fact of life. It hasn’t always been so power…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Thinking big-picture with A/B testing We’ve discussed A/B testing multiple times on this podcast, for good reason. But there’s an important angle we have yet to cover: in the life of a researcher or marketer, there’s no such thing as an A/B test. There’s an entire system …
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Using data science to help people write Using machine learning models to generate text, images, and other creative objects is, as they say, a bit of a hot topic right now. There are examples of models like this in action all across the internet and across different fields…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Writing code for computers and people No matter what sort of data science work you do, it’s fairly inevitable that you’ll have to write code to accomplish your goals. For substantial projects, it’s also fairly inevitable that you’ll have to work with other people to see t…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… What are data privacy and security? Data privacy and security are huge and hugely important topics — in all likelihood, you already know a little about them if you’re reading this intro. But they are both crucial to any good data science work, and this month we explore th…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Customer-focused research This month, we focus on research — but specifically research that’s aimed at your customers, delivering the sort of insight they would try to glean by running experiments and analysis using their own data. In particular, we dive into two differen…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Customer research: your secret weapon You can study as much mathematical theory, invent as sophisticated a machine learning model, or write as clean production-ready code as you want — if you don’t make sure you’re solving the right problems to begin with, all that effort…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Fuel for the Creative Fire It’s no secret: being creative is hard. Creativity requires time and energy, at the bare minimum, and lacking creativity can spiral into writer’s block and other such conditions. That may be okay if you’re just sending out a tweet here or there …
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Slow Problems, Quick Solutions We’ve devoted quite a bit of time on this podcast to robust, carefully tuned, and vetted-in-a-thousand-ways solutions. This episode, we venture beyond the land of neatly trimmed hedges and into the unknown, where scrappy solutions may be the…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Solving difficult problems with data science This month, we talk with Shane Suazo, the founder of Plytrix Analytics, about using data science to drive efficient business growth. Shane and Plytrix work with Vital Proteins, and we dive deep into their story and highlight th…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… (More) required reading for data science A question we frequently get asked is: what books should I read to be a better data scientist/machine learning engineer? This may not surprise you, but there isn’t just one answer — in fact, we spent an entire episode talking about…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Getting real value from data science This week, we talk with Ben Knox from Super Coffee and Gina Perrelli from Lunar Solar Group about using data science to motivate the growth of a business. No hypothetical business cases this week — Super Coffee is a real business with …
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Making your product experiments count We’ve talked about quite a few aspects of data science on this podcast, but one that’s perhaps conspicuously absent so far is running experiments on your product. It’s no secret that experiments provide extraordinarily high-quality da…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Recruiting for a data science team Most of us reading this writeup have probably had at least one interaction with a recruiter. Most of us reading this writeup probably don’t have a deep knowledge of recruiting — what recruiters do, how they help teams scale, and what the…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Required reading for data science A question we frequently get asked is: what books should I read to be a better data scientist/machine learning engineer? This may not surprise you, but there isn’t just one answer — depending on the skills you have, your knowledge base, t…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Understanding your Customer Lifetime Value This is a math-heavier episode than usual — we’re going to dive into probabilistic distributions and talk about systems of estimators. Even if that’s not your background, though, you should still find this episode useful. That di…
 
Benchmarks: what are they and why? You’ve probably heard of benchmarks. You’ve probably even used them. But what exactly are benchmarks, how are they useful, and how can you go about building a system to make benchmarks in your own industry? You’ll hear about all that and more, including: How to use benchmarks to make informed decisions about impro…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… 2020 Year in Review We have a bit of a different episode this month. Instead of diving deep into a specific topic, I asked 14 members of the Klaviyo data science team to give their personal highlight for 2020 as a year in data science. You’ll hear about a bunch of fascina…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Engineering Challenges in Data Science All data science work at scale rests on a solid foundation of engineering. We discuss how to establish that foundation — from what goes into software engineering to begin with to the specifics of how to prepare for big seasonal event…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Seasonality in e-commerce As the calendar changes, so do the right steps to take for your e-commerce business. We wade into the waters of seasonal changes in behavior, data, and logistics, and we take a deeper look at how to navigate them. You’ll hear from data scientists…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Recommender systems: how do they work? We get recommendations for all sorts of things today: routes to take when we drive, places to eat, books to read, petitions to sign, and of course, things to buy. We take a deeper look at the task of making the data science and softw…
 
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… What makes a report good? Data-centric teams likely take it as a given that good reporting is a key to living a happy life, but what exactly makes a report good? We dive into the topic of reporting and discuss ways to make a report exceed expectations. You’ll hear from da…
 
In this episode, we take a deep dive into a recent feature the team built, signup form A/B testing, to give you a taste of what it’s like to build software for data science. You’ll hear from data scientists, product designers, and software engineers. We discuss: The reason multi-arm bandits are called multi-arm bandits How to distill a two-minute e…
 
In this episode, we discuss how our careers in data science began, lessons we’ve learned along the way, and mistakes we’ve made and learned from. You can expect to hear: When we stopped wanting to be astronauts and started wanting to be data scientists Advice we’d give to anyone just starting in the field Advice we’d give to anyone currently at the…
 
We’re excited to unveil the first episode of the Klaviyo Data Science podcast! This podcast is intended for all audiences who love data science--veterans and newcomers alike, from any field, we’re all here to learn and grow our data science skills. We’re jumping right into the action with this episode. This is a deep dive into research in action. W…
 
Loading …

Hướng dẫn sử dụng nhanh

Google login Twitter login Classic login