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200+ design resources for developers by Brad Traversy @traversymedia github.com/bradtraversy/d…
i made over $25,000 building whop apps in last 6 weeks everyone is asking me: "what app do i build?" "what do i charge" "what do creators need?" im put together a 100% free guide with the 25 best whop app ideas RIGHT NOW rt + comment "GUIDES" and i'll send it over whop…
i built a tool that allows me to clone the brain of any youtuber… i used it on alex hormozi so i can ask him business questions at 3am and get answers word-for-word like he'd give them works with anyone: gary vee, naval, graham stephan, any creator in your niche i put…
A data scientist analyzed how often readers called a book “life-changing” vs how many reviews it had. Here were some outliers:
Google's (free) machine learning for trading online course (bookmark this one for later). Did I mention it's free? Grab it here:
UI/UX Designers, here are my favourites sites on the internet for design inspiration. Web Design → curated.design Landing Pages → landing.love Saas Websites → saaspo.com Navbar → navbar.gallery CTA Sections → cta.gallery…
This is still the way I recommend most people start with machine learning: 1. Start with Python 2. Learn to use Google Colab 3. Take a Pandas tutorial 4. Then a Seaborn tutorial 5. Learn how to use Decision Trees 6. Finish Kaggle's "Intro to Machine Learning" 7. Solve the…
(1/2) i felt like no one actually teaches you a good framework for how to read (ML) papers well + fast, so i wrote this 5-minute read tldr: because so many papers suck, here's how to go through them quickly and revisit the good ones
left: @Cloudflare design engineer right: @stripe design engineer same concept skill issue
This guy literally just leaked the largest prompt library ever created
AI Engineering Toolkit A curated list of 100+ LLM libraries and frameworks for training, fine-tuning, building, evaluating, deploying, RAG, and AI Agents. 100% Open Source
Karpathy spilled the formula of truly learning something: > don’t write blog posts > don’t do slides > write the code > arrange it > get it to work if you can truly build it you can say you know it. build from scratch guys.
she’s right. your ML projects don’t get you anywhere if you’re not working on the right set of problems. and she beautifully explains the levels of ML projects, from beginner, to ML engineer, to researcher, along with the set of skills you must target for each one.
They say don't judge a book by its cover... but in this case I think you can. How amazing does this look 🤩
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