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Credit card fraud detection, cancer prediction, customer churn prediction are some of the examples where you might get an imbalanced dataset. Training a model on imbalanced dataset requires making certain adjustments otherwise the model will not perform as per your expectations. In this video I am discussing various techniques to handle imbalanced dataset in machine learning. I also have a python code that demonstrates these different techniques. In the end there is an exercise for you to solve along with a solution link. Code: https://github.com/codebasics/deep-le... Path for csv file: https://github.com/codebasics/deep-le... Exercise: https://github.com/codebasics/deep-le... Focal loss article: https://medium.com/analytics-vidhya/h.... #imbalanceddataset #imbalanceddatasetinmachinelearning #smotetechnique #deeplearning #imbalanceddatamachinelearning Topics 00:00 Overview 00:01 Handle imbalance using under sampling 02:05 Oversampling (blind copy) 02:35 Oversampling (SMOTE) 03:00 Ensemble 03:39 Focal loss 04:47 Python coding starts 07:56 Code - undersamping 14:31 Code - oversampling (blind copy) 19:47 Code - oversampling (SMOTE) 24:26 Code - Ensemble 35:48 Exercise Do you want to learn technology from me? Check https://resources.codebasics.io/EhYhFF for my affordable video courses. Previous video: • Dropout Regularization | Deep Learning Tut... Deep learning playlist: • Deep Learning With Tensorflow 2.0, Keras a... Machine learning playlist : • Machine Learning Tutorial Python | Machine... 🌎 My Website For Video Courses: https://resources.codebasics.io/EhYhFF Need help building software or data analytics and AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website. #️⃣ Social Media #️⃣ 🔗 Discord: / discord 📸 Dhaval's Personal Instagram: / dhavalsays 📸 Instagram: / codebasicshub 🔊 Facebook: / codebasicshub 📝 Linkedin (Personal): / dhavalsays 📝 Linkedin (Codebasics): / codebasics 📱 Twitter: / codebasicshub 🔗 Patreon: https://www.patreon.com/codebasics?fa... DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.
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