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I’m excited to share that I’ve successfully completed the “Generative AI: Introduction and Applications” course on Coursera, authorized by IBM! 🎉 This learning experience helped me build a strong foundation in Generative AI—one of the most transformative areas in technology today. 🔍 What I learned: • The difference between generative and discriminative AI • Real-world capabilities and use cases of generative AI • Applications across industries and sectors • An overview of tools and models for generating text, code, images, audio, and video 🛠️ Skills gained: Artificial Intelligence & Machine Learning (AI/ML) | Generative AI | ChatGPT | AI Personalization | Real-Time Data I’m looking forward to applying these skills in practical projects and continuing my journey in AI. 🚀
https://www.coursera.org/account/accomplishments/verify/MPZFM01DJJF5
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IBM | 18,861,151 followers on LinkedIn. At IBM, we do more than work. We create. We create as technologists, developers, and engineers.
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Looks like the contra community is liking stuff on machine learning, and I thought it would be interesting to share another article we put together about why machine learning models can underperform for... just no obvious reason.
Despite having clean data and tuned hyperparameters, the accuracy graph barely moves.
The trick here is everything related to feature engineering. We wrote a piece titled “Feature engineering decides machine learning outcomes” to share our thoughts on this quasi-"mystic" exercise.
I call it quasi-"mystic" because it is part art and part science. You have to be able to see through the rubble of messy data and know what will really move the needle for you. Much like the jeweller in our cover.
It breaks down the essentials, from understanding your data’s structure to choosing well-validated features.
Read the full piece here: https://www.algorithmic.co/blogs/feature-engineering-decides-machine-learning-outcomes
Wow, this is sick. the cover as well as the article
8-yr-old me discovered castles and palaces through TV docs. Now, adult me is building new ways to explore them.
I built The Castle Hunting Atlas, a 3D globe that transforms historical exploration into an interactive, spatial experience.
Each node represents a real location, allowing you to orbit, discover, and step into architecture, memory, and heritage across the world.
Built 100% in Omma.
LinkedIn: https://bit.ly/4tuHIrX
That's a real vibe, man. Great idea. It looks amazing!
You know that moment when a client asks for a 3-email webinar sequence and you need it by tomorrow?
Stripo has an AI Hub built right into the editor. You describe what you need in a prompt, set your brand details (logo, tone of voice, audience), and it generates a full email sequence. Not just copy. Structure, layout, content blocks, styles.
Here's what makes it useful for freelancers specifically:
You control every step. The AI proposes, you decide. Edit the sequence structure, swap sections, regenerate parts you don't like. Pick from predefined color themes to match the client's brand in one click. Nothing ships without your say.
It also remembers your brand settings per project. So if you're working across multiple clients, each project keeps its own logo, tone, and audience. No mixing things up.
Right now it handles webinar series, digests, and promo campaigns. You go from a prompt to a ready-to-use email in minutes instead of hours.
Here's a quick walkthrough of the full process: https://www.youtube.com/watch?v=QsY5ZlHA82M
Have you tried using AI for email production yet, or are you still building everything from scratch?
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