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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
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
Matt Dancho (Business Science) Profile picture
May 28
Understanding regression models is essential in data science.

In 4 minutes, I'll demolish your confusion. Let's go: Image
1. The 6 Diagnostic Checks Every Data Scientist Should Run

Once you've built a regression model, your job isn't done. These 6 checks will tell you whether your model can actually be trusted.
2. Posterior Predictive Check

Ask yourself: do the model-predicted lines resemble the observed data line? If your model is a good fit, simulated data from it should look similar to your actual data. When they diverge wildly, your model is missing something important. Image
Read 9 tweets
Matt Dancho (Business Science) Profile picture
Apr 27
🚨 BREAKING: Microsoft launches a free Python library that converts ANY document to Markdown

Introducing Markitdown. Let me explain. 🧵 Image
1. Document Parsing Pipelines

MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. Image
2. Supported Documents

MarkItDown supports:

- PDF
- PowerPoint
- Word
- Excel
- Images (EXIF metadata and OCR)
- Audio (EXIF metadata and speech transcription)
- HTML
- Text-based formats (CSV, JSON, XML)
- ZIP files (iterates over contents)
- Youtube URLs
- EPubs Image
Read 7 tweets
Matt Dancho (Business Science) Profile picture
Apr 22
Understanding regression models is essential in data science.

In 4 minutes, I'll demolish your confusion. Let's go: Image
1. The 6 Diagnostic Checks Every Data Scientist Should Run

Once you've built a regression model, your job isn't done. These 6 checks will tell you whether your model can actually be trusted.
2. Posterior Predictive Check

Ask yourself: do the model-predicted lines resemble the observed data line? If your model is a good fit, simulated data from it should look similar to your actual data. When they diverge wildly, your model is missing something important. Image
Read 9 tweets
Matt Dancho (Business Science) Profile picture
Apr 19
Understanding probability is essential in data science.

In 4 minutes, I'll demolish your confusion.

Let's go! Image
1. Statistical Distributions:

There are 100s of distributions to choose from when modeling data. Choices seem endless. Use this as a guide to simplify the choice. Image
2. Discrete Distributions:

Discrete distributions are used when the data can take on only specific, distinct values. These values are often integers, like the number of sales calls made or the number of customers that converted.
Read 10 tweets
Matt Dancho (Business Science) Profile picture
Apr 18
RIP manual research workflows.

Someone just open-sourced what comes after Karpathy’s AutoResearch.

It’s called AutoResearchClaw.

And this thing is insane. Image
A few weeks ago, Karpathy showed where research was heading:

AI agents running the experiment loop.

That was already a big signal.

AutoResearchClaw takes it even further.

It doesn’t just help with research.

It tries to automate the entire scientific method end-to-end.
You give it a raw idea.

One CLI command.

Then it runs.

Not just “brainstorming.”

Not just “summarizing.”

Actually running the workflow.
Read 8 tweets

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