Launch Intel
De

Deepkit: the first desktop app for deep learning experiments

Hacker News

Deepkit: the first desktop app for deep learning experiments

https://deepkit.ai Hi guys, I'm the founder of Deepkit. An app that helps you visualize, debug, track, and run ML/DL experiments, directly on your workstation or on your own servers, in your LAN or in the cloud. Deepkit will be free for individual users and available in all app stores. You can use the app alone or use the real-time collaborative features within a team using the Deepkit team server. We're are looking for alpha users that want to help us building a better, cheaper and more efficient way of doing ML/DL experiments. If you're interested, please register at the website. We currently only support MacOS, but Windows & Linux will follow. Follow us on Twitter @deepkitAI to get notified once we release the public version. If you got any questions, I'm happy to answer in the comments.

Visit productView on Hacker NewsAug 26, 2019
Share card

Actual performance

3points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, user · Missing: agents, agent, cursor
83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: visualize, users, way · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: efficient, users · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Un
Unofficial ProtonMail Desktop App59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Unofficial ProtonMail Desktop App

Hacker News2
Sa
Saadhn – A Desktop App for JioSaavn63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Saadhn – A Desktop App for JioSaavn

Hacker News1
Pe
Perspec – Scriptable desktop app to correct the perspective of images62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Perspec – Scriptable desktop app to correct the perspective of images

Hacker News4
Pe
Perspec – Scriptable desktop app to correct the perspective of images62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Perspec – Scriptable desktop app to correct the perspective of images

Hacker News59
Bo
Bowery.io Desktop App74%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bowery.io Desktop App

Hacker News12
Th
The most enjoyable desktop app for writing a thesis63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The most enjoyable desktop app for writing a thesis

Hacker News8
I
I built a free desktop app for Clubhouse63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I built a free desktop app for Clubhouse

Hacker News2
De
Deep learning – Dropout with Theano66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Deep learning – Dropout with Theano

Hacker News5
De
Deep learning retreat scholarships70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Deep learning retreat scholarships

Hacker News1
Op
Optimizing deep learning algo with BLAS and Cython68%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Optimizing deep learning algo with BLAS and Cython

Hacker News2
Browse all productsAnalyze your launch