πŸ”₯ Matt Dancho (Business Science) πŸ”₯ Profile picture
Jul 30, 2022 β€’ 10 tweets β€’ 5 min read β€’ 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

Mar 25
Becoming an AI data scientist has levels to it.

Here's a complete roadmap: Image
Becoming an AI data scientist is a journey with multiple levels, each requiring specific tools and skills.

I’ve outlined a progression of levels with relevant skills and tools:
Level 1: Foundations of Data Science

- Python: Core programming language for data science (e.g., variables, loops, functions).
- Pandas: Data manipulation and analysis (e.g., DataFrames, cleaning data).
- NumPy: Numerical computations (e.g., arrays, linear algebra basics).
-Plotly: Data visualization (e.g., plotting charts, exploring trends).
- SQL: Querying databases for data extraction.Image
Read 7 tweets
Mar 24
Understanding P-Values is essential for improving regression models.

In 2 minutes, I'll crush your confusion.

Let's go: Image
1. The p-value:

A p-value in statistics is a measure used to assess the strength of the evidence against a null hypothesis. Image
2. Null Hypothesis (Hβ‚€):

The null hypothesis is the default position that there is no relationship between two measured phenomena or no association among groups. For example, under Hβ‚€, the regressor does not affect the outcome. Image
Read 13 tweets
Mar 23
Data scientists are out.

The Generative AI Data Scientist is in.

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 2025? Image
Read 5 tweets
Mar 23
Correlation is the skill that has singlehandedly benefitted me the most in my career.

In 3 minutes I'll demolish your confusion (and share strengths and weaknesses you might be missing).

Let's go: Image
1. Correlation:

Correlation is a statistical measure that describes the extent to which two variables change together. It can indicate whether and how strongly pairs of variables are related. Image
2. Types of correlation:

Several types of correlation are used in statistics to measure the strength and direction of the relationship between variables. The three most common types are Pearson, Spearman Rank, and Kendall's Tau. We'll focus on Pearson since that is what I use 95% of the time.Image
Read 11 tweets
Mar 22
Data Science for Business.

The book that helped me connect the dots. Let's dive in: Image
1. CRISP Data Mining Process

The foundation for applying data science to business is the CRISP method.

This is a helpful framework for integrating data science with the business understanding. Image
2. Machine Learning Predictions as Probabilities

One of the most important part of machine learning is probability.

We can estimate the probability from machine learning predictions.

Once you get this, the next framework opens up: Image
Read 7 tweets
Mar 21
90% of data scientists can improve their SQL for business intelligence.

In 3 minutes, learn the 20% of SQL gets 80% of results: Image
πŸ” SELECT Basics:

Start with SELECT * FROM table to retrieve all rows & columns.

Remember, SQL isn’t case-sensitiveβ€”but capitalizing keywords (SELECT, FROM) makes your queries easier to read. Image
πŸ“ Choosing Specific Fields:

Instead of the star (*), list only the fields you need (e.g., field1, field2) and rename them using AS for clarity.

Clear queries lead to clear insights. Image
Read 10 tweets

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