๐Ÿ”ฅ Matt Dancho (Business Science) ๐Ÿ”ฅ Profile picture
Jul 30, 2022 โ€ข 10 tweets โ€ข 5 min read โ€ข Read on X
How my life is changing as a direct result of attending the #RStudioConf ๐Ÿงต

#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-maโ€ฆ

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๐Ÿ”ฅ Matt Dancho (Business Science) ๐Ÿ”ฅ Profile picture

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More from @mdancho84

Dec 12
Some people really like Data Cleaning. I don't.

It takes me away from analyzing data. The fun part.

So I made an AI Agent to help. Image
The AI Agent contains 4 steps:

1. Create data cleaner code
2. Execute data cleaner code
3. If problem, fix code
4. Once fixed, explain code

Here's how it works:
1. In the first step, the AI analyzes an incoming data set.

Based on the features and statistics of the dataset, it creates code to perform a custom data cleaning.

Key skill: Python Code Generation Image
Read 11 tweets
Nov 16
Python has powerful time series libraries.

Case in point: skforecast

Let me explain: Image
Skforecast is a Python library for time series forecasting using machine learning models.

Skforecast works with any regressor compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others. Image
skforecast shines with probabilistic forecasting.

When trying to anticipate future values, most forecasting models try to predict what will be the most likely value.

This is called point forecasting.
Read 7 tweets
Nov 15
My favorite R package for ultra-fast exploratory analysis: Image
The R package is called correlationfunnel.

Yes, I built it.
What correlationfunnel does is:

* Speeds Up Exploratory Data Analysis

* Improves Feature Selection

* Gets You To Business Insights Faster Image
Read 6 tweets
Nov 14
The best beginner book on time series?

FPP: Forecasting Principles and Practice

Let's dive in: Image
Some may consider FPP the bible of time series.

I agree.

Start with FPP Version 2 or 3, and you won't go wrong.

This is what I like:
1. Time Series Visualizations

There's no better intuition for time series than a visualization.

- Time Plots
- Seasonal Plots
- ACF Plots

All are absolutely critical to understanding time series patterns. Image
Read 9 tweets
Nov 12
BEAST: A Bayesian Ensemble Algorithm for Change-Point Detection and Time Series Decomposition in R

Let's explore: Image
1. What is BEAST?

BEAST stands for Bayesian Estimator of Abrupt change, Seasonality, and Trend.

But what does that mean?
According to the authors, BEAST is a fast, generic Bayesian model averaging algorithm to decompose time series or 1D sequential data into individual components, such as abrupt changes, trends, and periodic/seasonal variations
Read 8 tweets
Nov 11
I used to struggle with working with Time Series.

After 10 years, I mastered it.

Then I spent 3 years making this R package so you can too: Image
The R package is timetk. I built it to make your life easier when working with Time Series:

- Plotting (Visualization)
- Data Wrangling
- Correlation
- Seasonality
- Imputation
- Outliers (Anomalies)
- Feature engineering
- Cross Validation
I'll focus on Time Series Plotting today.

1. Plotting Time Series: Use plot_time_series() Image
Read 12 tweets

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