Daily Dose of Data Science ✓

@DailyDoseOfDS_ · Join for free → · joined 29 May 2022

Delivering daily insights in DS, ML, RAGs, Agents & AI Engineering. Trusted by over 100k+ readers!

50 975Followers

2Following

2 730Posts total

183.5KViews on collected posts

Son gönderiler

Daily Dose of Data Science ✓@DailyDoseOfDS_16 Sep

RAG vs. Graph RAG vs. Agentic RAG, clearly explained! https://t.co/acpsahJexc

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1.4K views · 7 likes · 2 reposts · 0 replies Open on X →

Daily Dose of Data Science ✓@DailyDoseOfDS_15 Sep

LLMs break every assumption about regular ML inference. A traditional ML model such as a CNN, transformer classifier, or XGBoost model produces its output in a single forward pass. Nothing carries over between requests. The hardware performs roughly the same kind of work each h

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15.7K views · 205 likes · 49 reposts · 15 replies Open on X →

Daily Dose of Data Science ✓@DailyDoseOfDS_15 Sep

https://t.co/BLa1tqy0O0 29.4K views · 157 likes · 32 reposts · 6 replies Open on X →

Daily Dose of Data Science ✓@DailyDoseOfDS_14 Sep

Continuous batching in LLMs, clearly explained: (a popular LLM interview question; bookmark this) In traditional ML inference, a batch is a matrix. Every input is padded to the same length, one forward pass runs, and every row finishes at the same moment. LLM decoding does ht

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8.5K views · 120 likes · 21 reposts · 5 replies Open on X →

Daily Dose of Data Science ✓@DailyDoseOfDS_13 Sep

RLHF vs. DPO vs. GRPO, explained visually: https://t.co/wTXFPc4fci

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3K views · 32 likes · 4 reposts · 0 replies Open on X →

Daily Dose of Data Science ✓@DailyDoseOfDS_21 Oct 2025

@DailyDoseOfDS_ Your sharing of DS is amazing! I’d love to share DeepAnalyze, the first agentic LLM for autonomous data science, supporting: 🛠 Data Science & 🔍Data Research We’d really appreciate it if you could use your influence to post it. Code&Demo: https://t.co/1SeX5mulRh 367 views · 4 likes · 2 reposts · 0 replies Open on X →

Daily Dose of Data Science ✓@DailyDoseOfDS_28 Aug 2025

@DailyDoseOfDS_ If you’re requiring someone’s email address to download something that is “free” then it’s not really free when that information can be sold. 928 views · 4 likes · 0 reposts · 1 replies Open on X →

Daily Dose of Data Science ✓@DailyDoseOfDS_25 Sep 2024

@DailyDoseOfDS_ I couldn't find the the download link?? 2.7K views · 4 likes · 1 reposts · 0 replies Open on X →

Daily Dose of Data Science ✓@DailyDoseOfDS_23 Sep 2024

Get a FREE Data Science E-book (530+ page), featuring over 150 essential lessons in data science and machine learning. Download link in profile. https://t.co/qocCwAx98i

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121.6K views · 453 likes · 86 reposts · 23 replies Open on X →

Aynı büyüklükteki hesaplara karşı

Son 90 güne ait 5 gönderi, 10K–100K takipçi aralığıyla yan yana. aynı büyüklükteki hesaplardan daha çok kişiye gösteriliyor.

Medyan görüntülenme8 531bu hesap92410K–100K için medyan

Erişim, %16.74%bu hesap3.62%10K–100K için medyan

Etkileşim, %1.21%bu hesap1.52%10K–100K için medyan

Ölçüt	Bu hesap	10K–100K için medyan	Oran
Gönderi başına medyan görüntülenme	8 531	924	9.23×
Erişim (görüntülenme ÷ takipçi)	16.74%	3.62%	4.62×
Etkileşim oranı	1.21%	1.52%	0.79×

Bu aralıktaki diğer hesaplar → Başka bir hesapla karşılaştır → Bu kıyas değerleri nasıl kuruluyor →

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

121.6K23 Sep

2.7K25 Sep

92828 Aug

36721 Oct

3K13 Sep

8.5K14 Sep

29.4K15 Sep

15.7K

1.4K16 Sep

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.46%23 Sep

0.18%25 Sep

0.54%28 Aug

1.63%21 Oct

1.21%13 Sep

1.72%14 Sep

0.67%15 Sep

1.73%

0.66%16 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes39.9%986 in total

Reposts8.0%197 in total

Replies2.0%50 in total

Quotes0.3%8 in total

Bookmarks49.8%1 231 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.