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πŸ”₯ Matt Dancho (Business Science) πŸ”₯ Profile picture
@mdancho84
May 20, 2023 β€’ 7 tweets β€’ 5 min read β€’ Read on X
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As a data scientist, productivity is a 10X super power.

Here's a short list of AI tools to help data scientists with: 🧡

#ai #datascience #career #skills #tools Image
1. Writing code

AI pair programming is a huge benefit.

Tools like #chatgpt & github #copilot can help debug complex code and replace Googling + Stack Overflowing for common scripting.

Key skill: ChatGPT prompting (more on this in my free ChatGPT for Data Scientists) Image
2. Code Quality & Documentation

Great products have great documentation. AI can help produce documentation, comment code, and replace time-consuming manual documentation with automated AI docs.

Key Skill: Using @mintlify to build your docs: mintlify.com Image
3. Presentations

Great data scientists are storytellers. Use persuasion to your advantage.

Key Skill: Generating images with AI using @midjourney_ai . midjourney.com Image
I'm road-testing all of these.

And I've been quietly researching #ChatGPT for Data Scientists (My NUMBER 1 TOOL) for the past 4 months.

I have good news - I'm ready to reveal my chatgpt research!
If you want to understand how ChatGPT can make you a better data scientist (and mistakes to avoid)...

I'll be sharing my research in a Free WORKSHOP: ChatGPT for Data Scientists (Wednesday, June 7th)!
What's Your Next Step?

Join me and 1,000 data scientists as we crush AI in my LIVE ChatGPT for Data Scientists Workshop.

Seats are limited (1,000 max).

πŸ‘‰Register Here: us02web.zoom.us/webinar/regist… Image

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More from @mdancho84

πŸ”₯ Matt Dancho (Business Science) πŸ”₯ Profile picture
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
πŸ”₯ Matt Dancho (Business Science) πŸ”₯ Profile picture
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
πŸ”₯ Matt Dancho (Business Science) πŸ”₯ Profile picture
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
πŸ”₯ Matt Dancho (Business Science) πŸ”₯ Profile picture
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
πŸ”₯ Matt Dancho (Business Science) πŸ”₯ Profile picture
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
πŸ”₯ Matt Dancho (Business Science) πŸ”₯ Profile picture
Nov 9
R is crazy good at forecasting.

Just learn this R package: Image
The R package is modeltime (and yes, I created it).

Modeltime's goal is to make high-performance time series analysis easier, faster, and more scalable in R. Image
1. How modeltime works

Modeltime leverages the Tidymodels framework (like scikit learn but in R) to open up:

- ARIMA
- Exponential Smoothing
- Prophet
- Linear Regression
- Elastic Net
- XGBoost
(and more) Image
Read 10 tweets

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