KNN Algorithm In Machine Learning | KNN Algorithm Using Python | K Nearest Neighbor | Simplilearn

"️‍🔥Purdue - Professional Certificate in AI and Machine Learning - https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=4HKqjENq9OU&utm_medium=DescriptionFFF&utm_source=Youtube ️‍🔥IITK - Professional Certificate Course in Generative AI and Machine Learning - https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=4HKqjENq9OU&utm_medium=DescriptionFFF&utm_source=Youtube ️‍🔥Microsoft AI Engineer Program - https://www.simplilearn.com/ai-engineer-course?utm_campaign=4HKqjENq9OU&utm_medium=DescriptionFFF&utm_source=Youtube ️‍🔥Purdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=4HKqjENq9OU&utm_medium=DescriptionFFF&utm_source=Youtube" This KNN Algorithm in Machine Learningtutorial will help you understand what is KNN, why do we need KNN, and how KNN algorithm works using Python. You will learn how do we choose the factor 'K', when do we use KNN, with proper hands on demonstration to predict whether a person will have diabetes or not, using the KNN algorithm. Below topics are explained in this K-Nearest Neighbor Algorithm (KNN Algorithm) tutorial: 00:00 Introduction to KNN(K Nearest Neighbor) 00:57 Why do we need KNN? 02:33 What is KNN? 03:51 How do we choose the factor 'K'? 05:46 When do we use KNN? 06:42 How does the KNN algorithm work? 09:19 Use case - Predict whether a person will have diabetes or not? Dataset Link - https://drive.google.com/drive/folders/1YylTjWxmkUVdurMSDjl84dstCKZL6wH8 ✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH ⏩ Check out the Machine Learning tutorial videos: https://bit.ly/3fFR4f4 You can also go through the slides here: https://goo.gl/XP6xcp #KNNAlgorithmInMachineLearning #KNNAlgorithm #KNN #KNearestNeighbor #KNNMachineLearning #KNNAlgorithmPython #KNearestNegighborMachineLearning #MachineLearningAlgorithm #MachineLearning #Simplilearn When Do We Use the KNN Algorithm? The KNN algorithm is used in the following scenarios: ✅Data is labeled ✅Data is noise-free ✅Dataset is small, as KNN is a lazy learner Pros and Cons of Using KNN ✅Pros: Since the KNN algorithm requires no training before making predictions, new data can be added seamlessly, which will not impact the accuracy of the algorithm. KNN is very easy to implement. There are only two parameters required to implement KNN—the value of K and the distance function (e.g. Euclidean, Manhattan, etc.) ✅Cons: The KNN algorithm does not work well with large datasets. The cost of calculating the distance between the new point and each existing point is huge, which degrades performance. Feature scaling (standardization and normalization) is required before applying the KNN algorithm to any dataset. Otherwise, KNN may generate wrong predictions. ➡️ About Artificial Intelligence Engineer This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions. IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers. ✅ Key Features - Add the IBM Advantage to your Learning - 25 Industry-relevant Projects and Integrated labs - Immersive Learning Experience - Simplilearn's JobAssist helps you get noticed by top hiring companies ✅ Tools Covered - ChatGPT - Flask - Matplotlib - django - Python - Numpy - Pandas - SciPy - Keras - OpenCV - And Many More… 👉 Learn More At: https://www.simplilearn.com/applied-ai-course?utm_campaign=KNNInMLMachineLearning&utm_medium=Description&utm_source=youtube