Part of the reason that I love to take these courses (even if the content is review) is to see the different ways to accomplish a task. Udemy course: https://udemy.com/course/all-of-ai-chatgpt-midjourney-stable-diffusion-app-dev/ My notes: https://docs.google.com/document/d/15cA8-8qgi6N7RUIBbCB5ZohPaw1T0vN6MaZHxOSOYgw/edit?usp=sharing EDIT: The course was a nice refresher in prompt engineering, and I did learn a few really cool techniques. There was a...
While I have been working with RAG, agents and generative AI for a while, I wanted to get into the more advanced topics in this area. This is an advanced course and got great reviews, not to mention there were a few chapters that were in the areas that I would like to focus. Lets...
One of the things that I am noticing in the day job is that clients and potential clients are very interested to see if you have experience in their specific field. While each field may have its nuances when it comes to features, once you get past that machine learning is pretty common. That said,...
The previous course in this app left me longing for more, so I thought that I would take this course. I am really just looking for more experience dockerizing the apps that I am making so that I have more options other than what I am already doing. Udemy course: https://netrix.udemy.com/course/machine-learning-model-deployment-with-streamlit My Notes: https://docs.google.com/document/d/1uRrYU92LMdZkMAdNnDtf5ssWDg9ZeKGwvZzF14gU3II/edit?usp=sharing Overall,...
I am starting a project for a university that involves machine learning and cancer detection. Much of the project involves orchestration, but I wanted to get a refresher in this space. I did some of this kind of work last year, but I wanted to see what was new. Udemy course: https://www.udemy.com/course/mastering-deep-learning-for-cancer-detection My Notes: https://docs.google.com/document/d/1VUoRSLNDU4VHKog2bavXM-q3AqhtClbmoSuRliwLYuc/edit?usp=sharing...
The majority of my MLOps experience has been inside of Azure. More and more of my clients are coming to us looking for open-source or local solutions - it made sense to take a deeper dive into MLOps outside of Azure. Udemy course: https://udemy.com/course/sustainable-and-scalable-machine-learning-project-development/ My Notes: https://docs.google.com/document/d/1BJmdHvEG2vcnTBkdpRjFybIyXKr7Z6nCkzkSfoCeUJs/edit?usp=sharing UPDATE: I bailed on much of the second...
I started this course a while ago and got pulled away from it. I wanted to take it because there were a couple of use cases where I wanted to get experience. Also, I now have my new server set up with cuda support, so I am looking forward to creating some models with it....
I have done a little bit of everything that is being discussed in this course - local LLMs, RAG, Function calling, etc. I recently installed Ollama on my server and I have been creating local models. I wanted to bring it altogether. Udemy course: https://udemy.com/course/open-source-llms-uncensored-secure-ai-locally-with-rag/ My Notes: https://docs.google.com/document/d/1TUBsanbHoxOEvsDSJPCQzPTcvHVx3JfPDmbf2VOHVYk/edit?usp=sharing The course left me wanting, a bit. ...
