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🔥 Matt Dancho (Business Science) 🔥 Profile picture
@mdancho84
May 20, 2023 • 7 tweets • 5 min read • 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).

👉Register Here: us02web.zoom.us/webinar/regist… Image

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More from @mdancho84

🔥 Matt Dancho (Business Science) 🔥 Profile picture
Jul 1
🚨 Say goodbye to manual ETL

Cleaned a 100k-word PDF dataset in 3 lines of Python code: Image
1. What is DocETL?

DocETL is a system for LLM-powered data processing.

You can create LLM-powered data processing pipelines. Image
2. Quick Example:

I made a quick, messy-PDF-to-Structured Output pipeline in 3 lines of Python: Image
Read 7 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Jun 30
🚨 Synthetic Data is the Future of AI

Introducing The Synthetic Data Vault (SDV).

This is what you need to know: Image
Synthetic Data is the Future of AI

Synthetic data keeps your data private.

SDV generates fake datasets that look REAL.

Here's how: Image
I built a 100k-row customer dataset in 4 lines:

Perfect for HIPAA-compliant Machine Learning & AI.

Google Colab Example: colab.research.google.com/drive/1L6i-JhJ…Image
Read 7 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Jun 29
Logistic Regression is the most important foundational algorithm in Classification Modeling.

In 2 minutes, I'll crush your confusion.

Let's dive in: Image
1. Logistic regression is a statistical method used for analyzing a dataset in which there are one or more independent variables that determine a binary outcome (in which there are only two possible outcomes). This is commonly called a binary classification problem.
2. The Logit (Log-Odds):

The formula estimates the log-odds or logit. The right-hand side is the same as the form for linear regression. But the left-hand side is the logit function, which is the natural log of the odds ratio. The logit function is what distinguishes logistic regression from other types of regression.Image
Read 9 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Jun 27
These 7 statistical analysis concepts have helped me as an AI Data Scientist.

Let's go: 🧵 Image
Step 1: Learn These Descriptive Statistics

Mean, median, mode, variance, standard deviation. Used to summarize data and spot variability. These are key for any data scientist to understand what’s in front of them in their data sets. Image
2. Learn Probability

Know your distributions (Normal, Binomial) & Bayes’ Theorem. The backbone of modeling and reasoning under uncertainty. Central Limit Theorem is a must too. Image
Read 12 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Jun 27
🚨BREAKING: New Python library for Bayesian Marketing Mix Modeling and Customer Lifetime Value

It's called PyMC Marketing.

This is what you need to know: 🧵 Image
1. What is PyMC Marketing?

PyMC-Marketing is a state-of-the-art Bayesian modeling library that's designed for Marketing Mix Modeling (MMM) and Customer Lifetime Value (CLV) prediction.
2. Benefits

- Incorporate business logic into MMM and CLV models
- Model carry-over effects with adstock transformations
- Understand the diminishing returns
- Incorporate time series and decay
- Causal identification Image
Read 9 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Jun 26
Stop Prompting LLMs.
Start Programming LLMs.

Introducing DSPy by Stanford NLP.

This is why you need to learn it: Image
1. Why DSPy?

DSPy is the open-source framework for programming—rather than prompting—language models.

It allows you to iterate fast on building modular AI systems.
2. Modules that express AI programmer-centric way

To build enterprise-grade AI, you need to be able to build modular codebases.

DSPy makes it easy to create these LLM tasks modularly. Image
Read 8 tweets

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