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Jesper Dr.amsch :v_enby:

Jesper Dr.amsch :v_enby:✓ Add us as a preferred source on Google

Mastodon @jesper@tech.lgbt
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Make a deal with Jesper Dr.amsch :v_enby:

🔒 Paid proposals held safely in escrow — released only when the work's approved.

📣Sponsored postOne disclosed post (toot) with your link and message. $13→ 🧵Sponsored threadA multi-post explainer or story — the fediverse rewards depth over one-liners. $33→ 📦Product seeding / honest reviewSend me your product — I post a disclosed, honest take. Authenticity is the only ad this audience tolerates. $17→ 📌Pinned sponsored postA disclosed post pinned to the top of my profile for the month. $39/mo→ 🔗Profile link (bio field)Your link in one of my profile metadata fields for the month — native and low-key. $20/mo→ 🔁Boost packageI boost (repost) your account's toots through the month — distribution with zero content lift. $26/mo→ 🏛️Instance / community sponsorshipSponsor the server I run — a sponsor line in the About/rules and a welcome shout. A goodwill buy that keeps our community running. $33/mo→ 🤝Mutual boost collabWe boost each other across instances — a value swap between communities. Swap or paid→ 🎬UGC HireBranded content for your own channels & ads from $50→ 🎙️Podcast guest spotInvite Jesper Dr.amsch :v_enby: onto your podcast (~45 min, … $31→ 📞1:1 ConsultPaid video call — advice, coaching or Q&A $75/hr→

Every booking is a normal escrow-protected deal.

Followers
2.2K
Account age
3 yrs
🎁 Free analysisfor Jesper Dr.amsch :v_enby:
🕵️Fake Followers CheckReal-audience % & bot risk→ 📊Engagement rateBenchmarked vs. peers→ 💰What they chargeFair sponsored-post price→

Known for

💻 delta: 31.1 k ⭐ I read raw git diffs with no syntax highlighting for my entire career. delta made me realise how much context I was missing. delta is a Rust-powered pager that adds syntax highlighting, side-by-side views, line numbers, and word-level diff highlighting to git diff, blame, and grep output. 20+ themes, customizable styling, and it drops into your gitconfig as a one-line change. If 7 views 💻 delta: 31.1 k ⭐ I read raw git diffs with no syntax highlighting for my entire career. delta made me realise how much context I was missing. delta is a Rust-powered pager that adds syntax highlighting, side-by-side views, line numbers, and word-level diff highlighting to git diff, blame, and grep output. 20+ themes, customizable styling, and it drops into your gitconfig as a one-line change. If 💻 datasette: 11.1 k ⭐ I had a SQLite file I needed to share with non-technical colleagues. One command turned it into a searchable website. datasette generates a browsable web interface from any SQLite database — filtering, search, automatic REST APIs, and one-click deploys to the cloud. Plugin system for custom visualizations, authentication, and export formats. Even runs in the browser via WebAs6 views 💻 datasette: 11.1 k ⭐ I had a SQLite file I needed to share with non-technical colleagues. One command turned it into a searchable website. datasette generates a browsable web interface from any SQLite database — filtering, search, automatic REST APIs, and one-click deploys to the cloud. Plugin system for custom visualizations, authentication, and export formats. Even runs in the browser via WebAs I started writing down the ML papers and tools I was reading anyway. Turns out that's a newsletter. Late to the Party is my free weekly roundup of machine learning, data science, and Python -- no sponsors, no hype, just things I genuinely found useful that week. If your feed is mostly noise, this might help. Check it out here: http://amplt.de/SupportiveDraftyExtreme ┈┈┈┈┈┈┈┈✁┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈ 👋 Moi4 views I started writing down the ML papers and tools I was reading anyway. Turns out that's a newsletter. Late to the Party is my free weekly roundup of machine learning, data science, and Python -- no sponsors, no hype, just things I genuinely found useful that week. If your feed is mostly noise, this might help. Check it out here: http://amplt.de/SupportiveDraftyExtreme ┈┈┈┈┈┈┈┈✁┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈ 👋 Moi 💻 applied-ml: 29.6 k ⭐ We never stop learning in machine learning. Whenever I need to read up on a new topic, I go back to Eugene Yan's Applied ML list -- a curated collection of papers and tech blogs from companies sharing how they actually do data science and ML in production. Great resource for bridging the gap between academic ML and real-world systems. Check it out here: http://amplt.de/Everl4 views 💻 applied-ml: 29.6 k ⭐ We never stop learning in machine learning. Whenever I need to read up on a new topic, I go back to Eugene Yan's Applied ML list -- a curated collection of papers and tech blogs from companies sharing how they actually do data science and ML in production. Great resource for bridging the gap between academic ML and real-world systems. Check it out here: http://amplt.de/Everl

📊 Post engagement

Recent posts · likes + reposts
Jun 1latest
3
Avg engagement / post
2–4
Typical post (engagement)
0.1%
Engagement vs followers
75/100
Very consistent reach
Nov 2022
On Mastodon since
Half of recent posts land between 2 and 4 likes + reposts (median 3) — a dependable floor a sponsored post can count on.

🔥 Top post: 💻 delta: 31.1 k ⭐ I read raw git diffs with no syntax highlighti · 7 likes + reposts

📊 Activity & format

Posting cadence
0.9 / week
A lower-frequency account — each post lands with more weight.
Content mix
Mostly video
Recent: 0 text · 0 image · 12 video.
Follower / following
9×
Follows 246 back. A strong ratio — an audience that follows them, not a follow-for-follow network.

Recent posts

View on Mastodon ↗
▶ 🔥 Top post 💻 delta: 31.1 k ⭐ I read raw git diffs with no syntax highlighting for my entire career. delta made me realise how much context I was missing. delta is a Rust-powered pager that adds syntax highlighting, side-by-side views, line numbers, and word-level diff highlighting to git d… ★ 7
▶ I started writing down the ML papers and tools I was reading anyway. Turns out that's a newsletter. Late to the Party is my free weekly roundup of machine learning, data science, and Python -- no sponsors, no hype, just things I genuinely … ★ 4 ▶ 💻 openai-cookbook: 74.2 k ⭐ I keep coming back to this when I need a working API example, not a blog post. The OpenAI Cookbook is their official collection of Python examples and guides for common tasks: embeddings, function calling, fine-… ★ 2 ▶ My colleagues and I published the system I've been building at ECMWF. AIFS combines graph neural networks with a sliding window transformer, trained on 40 years of ERA5 data. It produces 10-day forecasts in about 2.5 minutes on a single GP… ★ 1 ▶ 💻 candle: 20.4 k ⭐ ML and Rust -- two worlds that keep getting closer. Candle is Hugging Face's minimalist ML framework for Rust. PyTorch-like syntax, GPU support via CUDA, and it runs in the browser through WASM. Ships with LLaMA, Whisper… ★ 3 ▶ The most instructive ML talks I've sat through were about failure. So that's the one I gave. At PyData Global 2020 I walked through real examples from science and industry where models collapsed on contact with production data. Distributio… ★ 3 ▶ From imaging North Sea oil fields to building ML weather models -- the path made no sense until it did. ECMWF published a profile about my work: how I went from a geophysics PhD to building AIFS, making the Anemoi framework more robust, an… ★ 1 ▶ I keep seeing people assume you need a huge team to build something meaningful. This list collects examples that say otherwise: Instagram had 13 employees at acquisition, WhatsApp had 55, Craigslist generates ~$1B/year with about 50 people… ★ 2 ▶ 💻 datasette: 11.1 k ⭐ I had a SQLite file I needed to share with non-technical colleagues. One command turned it into a searchable website. datasette generates a browsable web interface from any SQLite database — filtering, search, automat… ★ 6 ▶ 💻 applied-ml: 29.6 k ⭐ We never stop learning in machine learning. Whenever I need to read up on a new topic, I go back to Eugene Yan's Applied ML list -- a curated collection of papers and tech blogs from companies sharing how they actual… ★ 4 ▶ I spent years on this thesis, so naturally I put the whole thing online for free. It covers deep neural networks applied to 4D seismic data -- complex-valued networks, transfer learning for geophysics, and physics-informed approaches to re… ★ 2 ▶ 💻 distil-whisper: 4 k ⭐ Knowledge distillation doing what it does best. Hugging Face's distil-whisper takes OpenAI's Whisper and compresses it to 756M params (down from 1.55B), delivering 6x faster speech recognition while staying within 1… ★ 4

🐘 Community & instance

Home server
tech.lgbt
A LGBTQ+ tech server — its members and audience skew toward that niche, so expect a community-aligned, engaged following.
✅ Link-verified
Verified link
Proved ownership of a website linked on their profile — Mastodon's green-check verification, a real identity signal rather than a paid badge.
On Mastodon since
Nov 2022
Joined in the Twitter-exodus wave of late 2022 — part of the migration that made Mastodon a real destination.

💡 Facts

🗓️Joined Mastodon in 2022 — 3 years ago.
👁️Averages 3 views per post.
📤Posts about 0.9× per week.

🕵️ Fake follower check

Estimated
52/100
Fair Credibility score
76%
Mixed Real audience
Medium Fake-follower risk
High Data confidence
  • Est. 76% real, active audience · Medium fake-follower risk.
  • Low engagement (~0.1% of followers engage each post) — a sign of an inflated or inactive audience.
  • Verified account.
  • Established account (3+ years old).

Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.

About

I show you how to build better #AI in the real world. 🌦 Using #ML to predict Europe's weather at ECMWF 💾 Fellow Software Sustainability Institute #reproducibility 📚 Taught 13k+ #MachineLearning 🎥 #Youtube Partner 🥇 #Kaggle code #81 🎓 Phd from DTU Interested in: #ai #opensource #tech #careers I verified it myself. Turns out it's still me.

📸 Gallery

I started writing down the ML papers and tools I was reading anyway. Turns out that's a newsletter. Late to the Party is my free weekly roundup of machine learning, data science, and Python -- no sponsors, no hype, just things I genuinely found useful that week. If your feed is mostly noise, this might help. Check it out here: http://amplt.de/SupportiveDraftyExtreme ┈┈┈┈┈┈┈┈✁┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈ 👋 Moi 💻 openai-cookbook: 74.2 k ⭐ I keep coming back to this when I need a working API example, not a blog post. The OpenAI Cookbook is their official collection of Python examples and guides for common tasks: embeddings, function calling, fine-tuning, and more. Practical code you can run, not marketing copy. Good reference to bookmark even if you only use the API occasionally. Check it out here: http:/ My colleagues and I published the system I've been building at ECMWF. AIFS combines graph neural networks with a sliding window transformer, trained on 40 years of ERA5 data. It produces 10-day forecasts in about 2.5 minutes on a single GPU, runs four times daily alongside the physics-based IFS, and is publicly available under ECMWF's open data policy. This is what data-driven weather prediction l 💻 delta: 31.1 k ⭐ I read raw git diffs with no syntax highlighting for my entire career. delta made me realise how much context I was missing. delta is a Rust-powered pager that adds syntax highlighting, side-by-side views, line numbers, and word-level diff highlighting to git diff, blame, and grep output. 20+ themes, customizable styling, and it drops into your gitconfig as a one-line change. If 💻 candle: 20.4 k ⭐ ML and Rust -- two worlds that keep getting closer. Candle is Hugging Face's minimalist ML framework for Rust. PyTorch-like syntax, GPU support via CUDA, and it runs in the browser through WASM. Ships with LLaMA, Whisper, Stable Diffusion, and more. If you want ML inference without Python overhead or the GIL, this is the serious option. Check it out here: http://amplt.de/Definit The most instructive ML talks I've sat through were about failure. So that's the one I gave. At PyData Global 2020 I walked through real examples from science and industry where models collapsed on contact with production data. Distribution shift, leakage, and the things nobody warns you about in tutorials. Learn from other people's mistakes -- it's cheaper. Check it out here: http://amplt.de/Hila From imaging North Sea oil fields to building ML weather models -- the path made no sense until it did. ECMWF published a profile about my work: how I went from a geophysics PhD to building AIFS, making the Anemoi framework more robust, and bridging the gap between researchers and operational code. A look at what "scientist in ML weather forecasting" actually means day to day. Check it out here: h I keep seeing people assume you need a huge team to build something meaningful. This list collects examples that say otherwise: Instagram had 13 employees at acquisition, WhatsApp had 55, Craigslist generates ~$1B/year with about 50 people, and BuiltWith does $14M/year with a single employee. The Wright brothers are on there too. Good ammunition for the next time someone says your team is too smal

🔀 Audience overlap

Estimated

Estimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.

Tod Beardsley Tod Beardsley 18% Insider UA Insider UA 16% Jason Miller 🦊⚛️ Jason Miller 🦊⚛️ 14% arthur.pizza arthur.pizza 14% Anim Anim 13% diyelectromusic diyelectromusic 11%

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How many followers does Jesper Dr.amsch :v_enby: have?
Jesper Dr.amsch :v_enby: has 2,220 followers on Mastodon.

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