Hacker News: brockf

New comment by brockf in "A new replication crisis: Research that is less likely to be true is cited more"

brockf — Sat, 22 May 2021 14:44:07 +0000

This is most likely due to a selection process that favors either newsworthiness or trustworthiness. It’s a statistical artifact, see e.g. https://twitter.com/rlmcelreath/status/1396040993175126018?s...

Bias in machine learning: We can do better

brockf — Mon, 22 Jun 2020 17:40:27 +0000

Article URL: https://www.strong.io/blog/uncovering-bias-in-machine-learning

Comments URL: https://news.ycombinator.com/item?id=23603170

Points: 1

# Comments: 0

New comment by brockf in "Show HN: HuggingFace – Fast tokenization library for deep-learning NLP pipelines"

brockf — Mon, 13 Jan 2020 18:36:35 +0000

Most implementations are actually moving in the opposite direction. Previously, there was a tendency to look to aggregate words into phrases to better capture the "context" of a word. Now, most approaches are splitting words into sub-word parts or even characters. With networks that capture temporal relationships across tokens (as opposed to older, "bag of words" models), multi-word patterns can effectively be captured by attending to the temporal order of sub-word parts.

Designing, building, and shipping machine learning solutions: Three principles

brockf — Wed, 04 Dec 2019 06:26:24 +0000

Article URL: https://www.strong.io/blog/designing-shipping-machine-learning-principles

Comments URL: https://news.ycombinator.com/item?id=21700067

Points: 2

# Comments: 0

New comment by brockf in "Ask HN: Who is hiring? (December 2019)"

brockf — Mon, 02 Dec 2019 19:18:21 +0000

Strong Analytics | Chicago, IL | Full-time Data Scientists, Data Engineers | https://www.strong.io

We help companies integrate state-of-the-art machine learning into their products, internal tools, and infrastructure. We've designed, built, and deployed products in the automotive space, pharma, gaming, retail, tech, and many other verticals.

Requires an advanced degree (M.S./Ph.D.) in a quantitative science and 1+ years applying machine learning to real-world problems.

To apply: https://careers.strong.io/

New comment by brockf in "Prefrontal cortex as a meta-reinforcement learning system"

brockf — Tue, 15 May 2018 01:50:22 +0000

No reason to oversimplify and ignore a lot of important details — they're doing that for you!

Ask HN: Who is building something great in Vancouver, BC?

brockf — Sun, 24 Sep 2017 17:35:49 +0000

I keep hearing about this surging tech scene around here but rarely hear about any new startups. Who is building something up here in Vancouver?

Comments URL: https://news.ycombinator.com/item?id=15325646

Points: 4

# Comments: 0

New comment by brockf in "Twice as happy customers means half the marketing spend"

brockf — Fri, 23 Jun 2017 12:51:53 +0000

Survival modeling is exactly what's needed for these situations. It allows you to (a) consider censored data (i.e., active customers who you know stay for at least X months) and, (b) use flexible survival distributions beyond the standard exponential distribution assumed in the typical monthly churn rate calculations.

Source: Run a data science company and we work on a lot of customer lifecycle modeling projects with companies much younger than yours.

Leaving academia to start a data science company: Looking back at our first year

brockf — Mon, 12 Jun 2017 19:01:07 +0000

Article URL: https://medium.com/@brockferguson/leaving-academia-to-start-a-data-science-company-looking-back-at-our-first-year-33dab049d965

Comments URL: https://news.ycombinator.com/item?id=14540013

Points: 1

# Comments: 0

New comment by brockf in "Improving Stack Overflow jobs search with machine learning and R"

brockf — Wed, 31 May 2017 07:12:41 +0000

A quantile-based confidence interval from bootstrapping can yield a 100% confidence interval that does not contain 0, i.e., with 100% of cases positive/negative. But that does not (necessarily) mean that there is a 100% chance that the new version is better than the old one. Confidence intervals are not Bayesian credible intervals and cannot be treated as such. (That said, making some certain assumptions about the underlying model can in some times allow one to treat nonparametric bootstraps in such a way.)

Email optimization 101: How frequently should you email your customers?

brockf — Mon, 20 Mar 2017 20:27:30 +0000

Article URL: https://www.optimail.io/blog/email-optimization-how-frequently-email-customers

Comments URL: https://news.ycombinator.com/item?id=13917388

Points: 2

# Comments: 0

Why you should move beyond A/B testing for email campaign optimization

brockf — Sat, 18 Mar 2017 00:08:33 +0000

Article URL: https://www.optimail.io/blog/move-beyond-ab-testing-email-campaign-optimization

Comments URL: https://news.ycombinator.com/item?id=13899081

Points: 2

# Comments: 0

Predictive Model ROI ($) Calculator

brockf — Thu, 16 Mar 2017 13:57:19 +0000

Article URL: http://www.strong.io/blog/predictive-model-roi-calculator

Comments URL: https://news.ycombinator.com/item?id=13885009

Points: 1

# Comments: 0

New comment by brockf in "Show HN: My friends and I started a data science consulting firm after our PhDs"

brockf — Fri, 10 Mar 2017 02:30:24 +0000

Data security is hugely important. Here are a couple things we do to deal with it: (1) We cleanse the data of Personal Identifiable Information (PII) as quickly as possible (i.e., before it touches our servers), and (2) We host our databases behind secure networks and follow best practices with regards to authentication, encryption, etc.

New comment by brockf in "Show HN: My friends and I started a data science consulting firm after our PhDs"

brockf — Fri, 10 Mar 2017 02:27:18 +0000

We were all drawn to applying the statistical, experimental, and algorithmic approaches we learned in graduate school (and in our spare time) to a range of problems in industry. Every project has a big learning component that keeps things exciting and fresh.

Our first handful of clients all came from our professional network. I've been a developer and consultant for a long time (shockingly, over half my life!) and so, despite selling my companies and heading to graduate school, I had a bit of a network of other founders who knew me and were supportive of the new venture.

A few lessons learned, in brief: (1) Try really, really hard to be specific about what you offer (even when in reality you offer a lot of different things), (2) Write great proposals -- they become the project bible and really help streamline client conversations, and (3) Understanding a client's data and business always takes longer than you'd think.

Show HN: My friends and I started a data science consulting firm after our PhDs

brockf — Tue, 07 Mar 2017 15:22:54 +0000

Article URL: http://www.strong.io

Comments URL: https://news.ycombinator.com/item?id=13810969

Points: 8

# Comments: 5

New comment by brockf in "Testing an AI algorithm from concept to production"

brockf — Wed, 22 Feb 2017 15:20:44 +0000

Author, here. In this post, I review the various ways that we put our email marketing optimization algorithm to the test, starting from simple sim environments in R, to scrappy real-world tests, more complex simulations, and ultimately a private beta with a production app. I hope it helps those thinking of bringing their own algorithms to market, and would love any feedback!

Testing an AI algorithm from concept to production

brockf — Wed, 22 Feb 2017 15:14:51 +0000

Article URL: https://www.optimail.io/blog/validating-optimail-testing-ai-algorithm

Comments URL: https://news.ycombinator.com/item?id=13706067

Points: 7

# Comments: 1

New comment by brockf in "Ask HN: What are you working on and why is it awesome? 2017 Edition"

brockf — Sun, 19 Feb 2017 02:42:03 +0000

Hey thanks! I'm Jacob's co-founder at Optimail.

We only just launched yesterday, so I think we are still working to find that exact product-market fit. At the moment, however, we're targeting medium- to large-sized businesses that use drip email marketing campaigns, such as onboarding campaigns, lead nurturing campaigns, and retention campaigns.

Thanks for the feedback on the copy! If you are feeling extra generous and have a second, shoot me a PM and let me know what parts you found confusing. We want it to be accessible to non-technical marketers who might be using older software like Mailchimp, etc. (After all, a main benefit of using AI here is that you don't need to get into confusing automation-building stuff like multi-branching decision trees.)

New comment by brockf in "Show HN: Automatically optimize your drip email marketing campaigns using AI"

brockf — Fri, 17 Feb 2017 19:12:06 +0000

I'm excited to announce the public release of Strong Analytics' new product, Optimail.io. Optimail uses AI to send, manage, and optimize your drip email marketing campaigns. It's a replacement for complex decision trees, A/B split tests, and hours spent staring at your screen trying to make your email campaigns more effective.

After my first software business was acquired, I began my PhD in Cognitive Science at Northwestern University, where I was trained in statistics, research, machine learning, and experimental design. It was a blast! I met some amazing people, and I found the ideas I got to think about every day very exhilarating.

But what excited me even more was the possibility of integrating what I was learning about (machine learning, AI, optimization) with what I'd spend my life to that point building — software that helped people grow their businesses. So, I left academia and, together with a couple of fellow PhD friends from graduate school, have formed a data science development and consulting firm, Strong Analytics, and we are now launching Optimail as our first product.

If you do get a minute to check it out, I'd love to hear any feedback you have!