Quick Start to AI: Generative Models and Practical Use Cases
Machine learning can be a little confusing because there are so many options. But I just want something that will help me get started quickly. Having a working example as a starting point can accelerate my learning process.
Sure, there are tutorials, examples, and guides which are useful to get an overview. But for me, getting hands-on experience is critical to fully grasp an idea. Of course, watching this video doesn't count as hands-on experience, but it does offer a solid code example.
I'd prefer it to be simpler, but there are fundamental patterns we must recognize when exploring AI models. AI has widespread applications today, particularly in processing text, sound, images, and videos to generate outputs or work based on those inputs. Generative AI is indeed thrilling, given its versatility.
But it can be sluggish and costly. If our goal is specific, we don't need it. We don't need to sweat about prompts, the process of continuously tweaking the AI until it does exactly what we want.
For instance, feeding it examples for what we call 'shots'. This isn't necessary if training your own model for a specific task.
