Hey Champs ! Well, I was alking to one of my old friend and he is en excellent guy in data architecture and looking for someone who can do a live project with him for co-learning. If any is interested let me know I will just help both of you to connect. Purpose: 1. Need to learn complete AI model development lifecycle 2. Develop a project working on a real life use case. 3. Learn and share knowledge on dfferent aspects of AI.

Hi All, I found this video nice and informative explaining the foundations of ML and thought to share with you all hope you find it useful. https://youtu.be/BUTjcAjfMgY?si=rh3toh824A4rmd3k Don't forget to share your comments :)

Hey everyone! I've been learning and experimenting with prompt engineering recently - and I wanted to share something that's been really helping me. After testing different techniques with ChatGPT and other Al tools, I've built a personal structure that helps get the most accurate and useful results every time. Here's a snapshot of what I follow: Context - Who you are / what you're doing Specific Task - Clear and focused request Intent - What you want from the Al Format - Bullet points, para, table, etc. Limits - Word count or number of points Tone - Formal, friendly, urgent, etc. Example Output - Give a sample if possible Role Assignment - Ask Al to act like a senior/expert Chain of Thought - "Think step by step before answering" I've also handwritten all of this in my notebook to lock it in. Happy to share the photo or a clean version if anyone wants it Let's learn and build together.

Everyone’s talking about AI agents. But the truth? Most demos you see online are just that—demos. Even big players like Apple and Amazon struggle to make their AI features work in the real world due to issues like hallucinations and unreliable outputs. In this week’s video, I break down the differences between simple workflows and true AI agents and share practical strategies for building reliable AI systems, including: - How to use workflow patterns like prompt chaining and routing to solve real problems effectively - Why agent frameworks might not be the solution you think they are - The #1 thing you need to scale AI systems successfully (hint: it’s not a new tool) Learn how to move beyond the hype and build AI systems that actually work.

https://www.linkedin.com/posts/pratibha-kumari-jha_data-ai-ml-activity-7239840039403167744-jVOm?utm_source=share&utm_medium=member_desktop