Yes that's totally true, you learn best when you teach. Well, so... I started a YouTube channel to teach basic SQL 😅 And indeed learned some very basic things in the process. After trying to shoot and edit and etc etc, now I respect Dave (and other YouTubers) even more 🫡 Anyways. I linked to my first and only video for now. Feedback is very very welcome!

The goal of this group is to help you navigate the complex and rapidly evolving world of data science and artificial intelligence. This is your hub to stay up-to-date on the latest trends, learn specialized skills to turn raw data into valuable insights, connect with a community of like-minded individuals, and ultimately, become a Data Alchemist. Together, let's decode the language of data and shape a future where knowledge and community illuminate our way. Rules - Don't sell anything here or use Data Alchemy as any kind of funnel - We delete low effort community posts, and posts with poor English. Proofread your post first. - Help us make the posts high quality. If you see a low quality post, then click on the 3 dots on the post and "Report To Admins". Start by checking out these links - Classroom - Introduction - Roadmap - Contribution Be Aware of Scammers - Please be aware that this is a public group. Unfortunately, some people abuse the Skool platform to send DMs or post comments to trick people. This is the internet, so always do your own due diligence. Never automatically trust someone here on the Skool platform other than @Dave Ebbelaar's official account. To kick things off, please comment below, introducing yourself. Let us know: 1. Your name and where you're from 2. What project(s) you're currently focused on See you in the comments!

- Meta's releasing Llama 3.2, which includes small and medium-sized vision LLMs (11B and 90B), and lightweight, text-only models (1B and 3B) that fit onto edge and mobile devices, including pre-trained and instruction-tuned versions. - The Llama 3.2 1B and 3B models support context length of 128K tokens and are state-of-the-art in their class for on-device use cases like summarization, instruction following, and rewriting tasks running locally at the edge. These models are enabled on day one for Qualcomm and MediaTek hardware and optimized for Arm processors. https://ai.meta.com/blog/llama-3-2-connect-2024-vision-edge-mobile-devices/

Hello everyone! this is my first post on this community so i am really sorry if i did something wrong :) Today i just finished Phyton Fundamentals from kaggle that the Classroom recommended and actually, before this i have already done some Phyton course from learnphyton.org. But even after i finish both of this Phyton course i still feels like there is something that's not right in me. Everytime i do an exercise that the course provide if the exercise is too hard i ended up just going for the hint or asking ChatGPT for help or even worse just going straight into the solution. Which make me feels like i haven't really mastered the basics of Phyton. Well, that is my problem right now, i planned to just go forward and continuing the Classroom right now but if any you have insights/tips/recommendations to be shared with me, it will be really helpful and appreciated. Thanks for reading this post.

I just completed the simple app example from the LangChain docs, they have really made langchain much more intuitive to use! There are so many ideas running through my head on what I could more easily accomplish with the LangChain ecosystem.