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🔥 Matt Dancho (Business Science) 🔥 Profile picture
@mdancho84
May 20, 2023 • 10 tweets • 5 min read • Read on X
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BIG ANNOUNCEMENT: I'm beyond excited to announce that in 5 days, I'm launching my brand new course- The #Python for Machine Learning & API's Course.

This course will transform your #career.

Here's what's inside... 🧵

#datascience #course Image
This launch marks the culmination of 2 years of research...

It covers The 6 Top #Python libraries for machine learning and production:
1. #Pycaret: Low-code machine learning Image
2. #ScikitLearn: The premier ML toolkit in Python Image
3. #H2O: Blazing speed + AutoML Image
4. #MLFlow: Easy model lifecycle management Image
5. #FastAPI: Incredibly fast + easy APIs in python Image
6. #Streamlit: Simplified data science web apps Image
Ready to learn more AND advance your career with Python?

Then you can't miss this event.

$400 in giveaways that everyone gets for attending live!
What's the next step?

Just join my course waitlist + live launch event here.

I'm super excited!! 😀

👉Register Here: learn.business-science.io/python-ml-apis… Image

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More from @mdancho84

🔥 Matt Dancho (Business Science) 🔥 Profile picture
Aug 13
Data Scientists: It's not how good you are at ChatGPT.

It's how good you are at combining your knowledge with ChatGPT.

Let me explain. Image
A common misconception is that Data Scientists think ChatGPT will do their job for them.

In my experience, this is wrong.

Yes- ChatGPT is very helpful.

But it's not human-level intelligence.
Case in point: ChatGPT skips important steps.

I was working on a data science project.

I asked ChatGPT to make an ML Model and a Shiny Web App.

ChatGPT did exactly what I asked.

Why is this a problem? Let's find out...
Read 6 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Aug 7
Can ChatGPT be used for Time Series in R?

I've had success with using Chatgpt for about 80% of my time series code.

Here's how I got my projects to 100% with chatgpt. 🧵 Image
ChatGPT is a game changer for time series. No question.

But is it perfect? Hardly.

Things I've experienced (and overcame):
1. ChatGPT is great for starter time series code. But you still will need to rework (aka debug).

The best way to avoid rework is to be explicit.

Here's an example prompt that details how I request time series code from ChatGPT. Image
Read 7 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Aug 6
Stop making R Shiny Web Apps from scratch.

Use ChatGPT instead.

This is how (Step 2 is the best). 🧵 Image
R Shiny Web Apps take me days to build when I make them from scratch.

ChatGPT has been my secret weapon.

I use a special technique called Prompt Stacking, which is a simple idea.

Here's how Prompt Stacking works:
Step 1. Start with a basic prompt.

Example:

"Create a foundational shiny app that allows upload of user's Excel files."
Read 6 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Aug 5
Correlation is the skill that has singlehandedly benefitted me the most in my career.

In 3 minutes I'll compress what I learned in 10 years of using correlation to solve business problems.

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.
2. Types of correlation: There are several types of correlation 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 95% of the time what I use.
Read 11 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Aug 4
Top 5 books on data science.

Let's dive in: Image
1. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems Image
2. Data Science for Business Image
Read 7 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Jul 31
For years, I was hyperparameter tuning XGBoost models wrong.

In 3 minutes, I'll share one secret that took me 3 years to figure out. 

When I did, it cut my training time 10X. Let's dive in: Image
1. XGBoost:

XGBoost (eXtreme Gradient Boosting) is a popular machine learning algorithm, especially for structured (tabular) data. It's claim to fame is winning tons of Kaggle Competitions. But more importantly, it's fast, accurate, and easy to use. But it's also easy to screw it up.
2. Hyperparameter Tuning:

To stabilize your XGBoost models, you need to perform hyperparameter tuning. Otherwise XGBoost can overfit your data causing predictions to be horribly wrong on out of sample data.
Read 10 tweets

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