Allie K. Miller’s Post

Great opportunity for anyone who wants to learn but may not know where to start in regards to AI.

Still struggling to understand AI? Follow Allie! Her new course is certain to help break down the best tools and actions you need to take in a way that is easy to understand and implement.

It is God’s♥️♥️♥️will to let me know this fucking awesome game!!!🤣🤣🤣From dreaming about it to knowing it and wanting to become a specialist at it.😆😆😆 I♥️♥️♥️God♥️♥️♥️.(I love this game and I can learn the game from learning AI.)

Happy Monday Gang... Quick plug, for those of you that have been getting more and more confused with all the AI terms. The Intro to GenAI course from Google is a great starting point to understanding AI/ML/Deep Learning/Generative AI. It gave me a foundational understanding, but I know which sub-topics to dive deeper into. I’m happy to share that I’ve obtained a new certification: Introduction to Generative AI from Google!

In Part 2 of the new Coursera course "Fundamentals of Generative AI for Beginners" at https://lnkd.in/g5Q9xb-4 by Curtis Evans you'll jump into the History of Generative AI. It's always a good idea to have an idea of where a 'new' field of inquiry is actually coming from, so let's take a look at: - The History of Generative AI - The Birth of Artificial Intelligence - The Rise of Deep Learning - The First Forms of Generative AI What's old is new again, the wheel keeps turning... Let's learn about it together

Hello connections, I am happy to share this information with you all that I've successfully completed the online 𝒔𝒌𝒊𝒍𝒍𝒊𝒏𝒈 𝒄𝒐𝒖𝒓𝒔𝒆 on 𝐀𝐈 𝐟𝐨𝐫 𝐈𝐧𝐝𝐢𝐚 𝟐.𝟎 from Guvi. https://lnkd.in/gnbY7h7N https://lnkd.in/gRm_fySG I have learnt the basic concepts of AI, ML and Deep Learning. With the hands-on models and projects provided by the course, I could learn a lot about the working and functions of AI in the modern world.

2 modules down, 2 more to go...here's a brief summary for Part 3 of the Fundamentals of Generative AI for Beginner's class available on Coursera.

Just finished this amazing course! 😜 It's incredible to see the potential of building upon foundational Large Language Models (LLMs) and the new challenges of Generative AI. It's like the electricity of this new era! Every business will need its own reasoning engine to enhance its capabilities with AI applications. 🧠👾🦾 Thanks to DeepLearning.AI for providing such great and up-to-date content.

I don't suspect most people will have to get this deep into learning about generative AI. But if you are interested in building something in this space, then i'd encourage folks to brush-up on statistics 101 and probability theory. You will read/see a lot of conditional probabilities in papers and talks especially around generative AI. For example, the image below in an excerpt from a paper that talks about the conditional probability of generating Y text given some source text X. In this case its a machine translation/transduction task. So what are conditional probabilities? There are a lot of online references you can use to learn about them. But you must learn Baye's Theorem. For now, i'll leave some quick reference links, but dive deeper here next week https://lnkd.in/gZwd5E9c https://lnkd.in/gt_hzzR9

Let's talk about Part 3 of this interesting new course for beginners to learn about Generative AI, that hot topic on everyone's mind these days. https://lnkd.in/g5Q9xb-4 by Curtis Evans. In Part 3 of 4, we discover the growth of Generative AI and learn fundamental concepts and vocabulary including: 🎶 Using data to generate quality output 🎶 How these text-based models are built 🎶 Transformers, embeddings, positional encoding, and self-embeddings The nice thing about this course is the use of solid examples to drive home concepts and help you remember vocabulary. I drew a chubby LLM who's ingested a lot of data as a visual cue :)