Image credit: hbr.org Here I covered a detailed and beginner friendly explanation of some of the most powerful prompting techniques. Zero Shot Prompting: In zero shot prompting, the model receives a direct instruction without any examples. It’s like asking a question to someone who’s never seen a similar one before and hoping they understand the […]
Image Credit: dataconomy When training a machine learning model, one of the most common question is, How many epochs should I run? The answer isn’t always straightforward. An epoch refers to one complete pass of the training dataset through the model. Running multiple epochs can bring big benefits, but also big risks if not handled […]
As AI becomes smarter, it is easy to assume machines can work entirely on their own. But in reality, even the best models need a human touch. That’s where Human in the Loop (HITL) comes in. It is a process where humans actively guide, review and fine tune the AI, especially in situations where data […]
Image credit: otalk9focus Reinforcement Learning (RL) is a core pillar of modern AI systems. It mimics how human learn by trying, receiving feedback, and improving over time. (To better understand RL, think of how dogs are trained with rewards and penalties.) Unlike supervised learning, where models learn from labeled datasets, RL allows AI to explore […]
Image credit: nature In AI, learning isn’t one-size-fits-all. Models learn from data in different ways, and understanding the three core types – supervised, unsupervised and deep learning (descriptive learning) – can help us better grasp how modern AI powers everyday applications, especially recommendation systems on platforms like Netflix and Amazon. Supervised learning is like training […]
Image credit: statsig Fine tuning the behavior of an AI model is not just about writing the right prompt-It is also about adjusting the temperature behind the scenes. In LLMs temperature controls how creative or focused the model’s output will be. A lower temperature such as 0.0-0.2 keeps the response consistent, fact based and deterministic, […]
Image Credit: Encord Fine tuning parameters in AI models is more than adjusting dials- it’s about aligning the model’s behavior with real world need. When dealing large and dynamic datasets, especially in industries like retails, the right parameter tuning ensures that outputs are not accurate but context aware. Instead of relying on default settings, adjusting […]