Matt Dancho (Business Science) Profile picture
Jul 30, 2022 10 tweets 5 min read Read on X
How my life is changing as a direct result of attending the #RStudioConf 🧵

#rstats
Just 3 days ago, I had the pleasure of watching the #rstudioconf2022 kick off.

I've been attending since 2018 and watching even longer than that.

And, I was just a normal spectator in the audience until this happened.
@topepos and @juliasilge's keynote showed all of the open source work their team has been working on to build the best machine learning ecosystem in R called #tidymodels.

And then they brought this slide up.
Max and Julia then proceeded to talk about how the community members have been working on expanding the ecosystem.

- Text Recipes for Text
- Censored for Survival Modeling
- Stacks for Ensembles

And then they announced me and my work on Modeltime for Time Series!!!
I had no clue this was going to happen.

Just a spectator in the back.

My friends to both sides went nuts. Hugs, high-fives, and all.

My students in my slack channel went even more nuts.
Throughout the rest of the week, I was on cloud-9.

My students that were at the conf introduced themselves.

Much of our discussions centered around Max & Julia's keynote and the exposure that modeltime got.
And all of this wouldn't be possible without the support of this company. Rstudio / posit.

So, I'm honored to be part of something bigger than just a programming language.

And if you'd like to learn more about what I do, I'll share a few links.
The first is my modeltime package for #timeseries.

This has been a 2-year+ passion project for building the premier time series forecasting system.

It now has multiple extensions including ensembles, resampling, deep learning, and more.

business-science.github.io/modeltime/
The second is my company @bizScienc.

For the past 4-years I've dedicated myself to teaching students how to apply data science to business.

I have 3000+ students worldwide.

Here are some of my tribe that I met at #rstudioconf2022.
The third is my 40-minute webinar.

I put a free presentation together to help you on your journey to become a data scientist.

A few things I talk about:

Modeltime for Time Series.
Tidymodels & H2O for Machine Learning
Shiny for Web Apps
and 7 more!

learn.business-science.io/free-rtrack-ma…

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More from @mdancho84

Jul 14
RIP Data Scientists.

The Generative AI Data Scientist is NOW what companies want.

This is actually good news. Let me explain: Image
Companies are sitting on mountains of unstructured data.

PDF
Word docs
Meeting notes
Emails
Videos
Audio Transcripts

This is useful data. But it's unusable in its existing form. Image
The AI data scientist builds the systems to analyze information, gain business insights, and automates the process.

- Models the system
- Use AI to extract insights
- Drives predictive business insights

Want to become a Generative AI Data Scientist in 2026? Image
Read 4 tweets
Jul 13
This is huge.

A group of 50 AI researchers (ByteDance, Alibaba, Tencent + universities) just dropped a 303 page field guide on code models + coding agents.

And the takeaways are not what most people assume.

Here are the highlights I’m thinking about (as someone who lives in Python + agents):Image
1) Small models can punch way above their weight

If you do RL the right way (RLVR / verifiable rewards), a smaller open model can close the gap with the giants on reasoning-style coding tasks.
2) Python is weirdly hard for models

Mixing languages in pretraining helps… until it doesn’t. Python’s dynamic typing can create negative transfer vs. statically typed languages. Meanwhile pairs like Java↔C# or JS↔TS have strong “synergy.”
Read 13 tweets
Jun 30
A senior Google engineer dropped a 482 page PDF on agentic design patterns.

482 pages.

Most AI engineers bookmarked it and never opened it again.

I read the whole thing.

Here are the top 5 patterns (explained in plain English): Image
PATTERN 1 — Single Agent

The simplest and most common starting point.

One model. One system prompt. A bounded set of tools.

The model decides which tool to call, observes the result, and keeps going until it has enough to answer. Image
PATTERN 2 — Multi-Agent Sequential

Specialized agents run in a fixed order.

Each one's output feeds the next one's input. Image
Read 8 tweets
Jun 9
🚨BREAKING: Google just DROPPED a masterclass on GPUs

Get it here 100% free: Image
FULL GUIDE: HOW TO SCALE YOUR MODEL: jax-ml.github.io/scaling-book/

PART 12: HOW TO THINK ABOUT GPUS: jax-ml.github.io/scaling-book/g…

I have one more thing before you go.

If you want to become a generative AI data scientist in 2026 ($200,000 career), then I'd like to help: Image
On June 24th, I am hosting a free workshop to help you get started with AI + DS projects in Python.

Register here (500 seats):   learn.business-science.io/ai-registerImage
Read 4 tweets
Jun 5
This 277-page PDF unlocks the secrets of Large Language Models.

Here's what's inside: 🧵 Image
Chapter 1 introduces the basics of pre-training.

This is the foundation of large language models, and common pre-training methods and model architectures will be discussed here. Image
Chapter 2 introduces generative models, which are the large language models we commonly refer to today.

After presenting the basic process of building these models, you explore how to scale up model training and handle long texts. Image
Read 8 tweets
May 29
RIP document extractors.

Google just released LangExtract: Open-source. Free. Better than $100K enterprise tools.

Here’s what it does: 🧵 Image
What it does:

→ Extracts structured data from messy text
→ Grounds every field to the exact source location
→ Handles 100+ page docs
→ Generates interactive HTML for verification
→ Works with Gemini + local models Image
What it replaces:

→ Regex/fragile parsing
→ Custom NER pipelines
→ Expensive extraction APIs
→ Manual data entry Image
Read 7 tweets

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