100 Days of Machine Learning | CampusX - Instance-Based Vs Model-Based Learning | Types of Machine Learning

The Machine Learning systems which are categorized as instance-based learning are the systems that learn the training examples by heart and then generalize to new instances based on some similarity measure. It is called instance-based because it builds the hypotheses from the training instances. It is also known as memory-based learning or lazy learning. The time complexity of this algorithm depends upon the size of training data. The worst-case time complexity of this algorithm is O (n), where n is the number of training instances. A system is called model-based when it learns from the data and creates a model, which has some parameters and it predicts the output by using this data trained model. ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in/s/store ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at [email protected] ✨ Hashtags✨ #100DaysOfMachineLearning #MachineLearningFullCourse #MachineLearningInHindi ⌚Time Stamps⌚ 00:00 - Intro 00:50 - Instance vs Model Based Learning 03:00 - Instance based Learning 07:45 - Model based Learning 11:20 - Differences 16:30 - Outro