Towards Data Science ✓

@TDataScience · We're Global 🌏 · joined 20 Oct 2016

The world's leading publication for data science and artificial intelligence professionals. Submit an Article ✍️ https://t.co/57pIMegK1o

251 128Followers

1 919Following

64 167Posts total

18.8KViews on collected posts

Latest posts

Towards Data Science ✓@TDataScience13 Sep

"You will learn how to parameterize weight distributions, run variational inference, and extract actionable uncertainty bounds that reveal exactly when your model should and shouldn't be trusted." Tom Narock presents a hands-on introduction to Bayesian neural networks and their 1K views · 2 likes · 1 reposts · 1 replies Open on X →

Towards Data Science ✓@TDataScience13 Sep

We usually think of missing data as a problem that needs to be solved or an absence that needs to be filled. David Conneely makes a well-argued case for the intrinsic value of missingness and what it can reveal about the data we observe. https://t.co/5rMuyYMRne 3.4K views · 9 likes · 0 reposts · 0 replies Open on X →

Towards Data Science ✓@TDataScience13 Sep

From enum and array hallucinations to distributional collapse, Mostafa Ibrahim outlines the various ways that LLM structured outputs can look right on the surface while hiding serious, hard-to-catch data errors. https://t.co/sQ2LMVgRpm 3.5K views · 5 likes · 0 reposts · 0 replies Open on X →

Towards Data Science ✓@TDataScience12 Sep

An API that ingests 10,000–20,000 developer-community posts a day and turns them into keyword trends, sentiment, and sourced summaries — for about $30–40 a month. By Ida Silfverskiold https://t.co/xWgvJ9URQn 4.3K views · 7 likes · 0 reposts · 0 replies Open on X →

Towards Data Science ✓@TDataScience12 Sep

In a thorough, hands-on deep dive, @tahreemrasul1 presents a framework for building RAG pipelines that introduces complexity in response to observed failure modes, from lexical and hybrid search to reranking and agentic information seeking. https://t.co/TIoZrRbFwJ 3.9K views · 6 likes · 0 reposts · 0 replies Open on X →

Towards Data Science ✓@TDataScience23 Feb 2025

📢 CALLING ALL AUTHORS 📢 Share your data science insights and get published on Towards Data Science. Tap the link to learn more. https://t.co/ympeAXAkwj 2.8K views · 11 likes · 2 reposts · 0 replies Open on X →

Against accounts of the same size

5 posts from the last 90 days, next to the 100K–1M follower range. ordinary reach for its size, weaker reaction than most.

Median views3 483this account5 898median for 100K–1M

Reach, %1.39%this account1.59%median for 100K–1M

Engagement, %0.16%this account1.04%median for 100K–1M

Metric	This account	Median for 100K–1M	Ratio
Median views per post	3 483	5 898	0.59×
Reach (views ÷ followers)	1.39%	1.59%	0.87×
Engagement rate	0.16%	1.04%	0.16×

Others in this range → Compare with another account → How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

2.8K23 Feb

3.9K12 Sep

4.3K

3.5K13 Sep

3.4K

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.47%23 Feb

0.16%12 Sep

0.16%

0.14%13 Sep

0.27%

0.39%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.04%.

What the audience does

Likes55.6%40 in total

Reposts4.2%3 in total

Replies1.4%1 in total

Bookmarks38.9%28 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Latest posts

Against accounts of the same size

Growth & engagement

Views per post

Engagement rate per post

What the audience does

Similar accounts