
Machine Learning, Deep Learning and Data Science simplified and served to your coffee break☕!
| Platform | Pricing | Only free issues | Publishes | Weekly | |
|---|---|---|---|---|---|
| Issues | 56 | Founded | 2 years ago | Last Issue | 10 days ago |
| Active | |||||

Imagine you process B2B order forms every day. In theory, all documents contain the same information:
customer ID
purchase order number
delivery date
ordered items
In practice, however, every customer structures the...
Chunk Size 220
Q2: “How does OneLatex interpret text highlighted in green in OneNote?”
Answer: “If the background of a text in OneNote is marked in yellow, OneLatex interprets the text as native LaTeX code…”Chunk Size 500...
Could I build a small plot agent that understands natural language, picks the right tools and instantly returns the right answer or visualization?
I decided to find out. The result was a simple CSV Plot Agent with LangChain, Streamlit and...
When you get a new CSV, what do you check first?
Typical questions are:
Which columns does the dataset contain?
Are there columns with missing values (NaNs)?
What do the descriptive statistics of the numerical columns look l...
🍕 Always choose the best pizzeria you already know?
That’s the greedy strategy: Safe, but you might be missing something even better.
This is the Exploration vs. Exploitation dilemma in action.
In AI, it’s tackled with Multi-Armed Bandi...
Subscribers, engagement, traffic and sponsorship for Data Science Espresso by Sarah Lea.
| Subscribers | Engagement | 61 | Monthly Web Visits | ||
|---|---|---|---|---|---|
| Accepts Sponsors | Estimated Cost per Ad | ||||
The writers behind this newsletter.
Simplifying tech for curious minds | Follow for insights that make tech accessible \ud83d\ude80 | Writing about Data, AI, ML & Python | MSc in Data Science in Progress | Ex-Salesforce-Consultant, now working at a Big Tech company
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