Majority of the machine learning courses assume the availability of labeled training data as it’s crucial for supervised machine learning models. But, labeled data rarely exists in the real world. We need to collect labels and labeling data is hard and costly, without labels there is no model. So what’s the solution? Active Learning: We need to build a model to label...
Complex domains have a rich relational structure which can be represented as a relational graph consisting of entities and relationships. Graphs are a language built on graph data structures to describe and analyze entities with relations/interactions. Many types of data are graphs. Social networks Communication networks Internet Knowledge Graphs Research paper citation networks Molecules And many more. We can take advantage...
As the post-pandemic world is pushed more towards engaging customers online, leveraging chatbots and messengers has become a priority for organizations. But a chatbot with few static lines of fixed responses is not sufficient to handle the dynamics of customer conversations. If you want to create a successful automated chat program using Rasa, you need to understand how it functions....
Classification is a very common use case in machine learning and is taught in many courses with somewhat balanced datasets, but many real-world use-cases have datasets with an imbalanced distribution of categories/classes to be classified. Standard approaches for balanced classification will give the illusion of good accuracy when accuracy itself becomes a misguiding metric for evaluation when data has...
