pstrongIntegrate scikit-learn with various tools such as NumPy, pandas, imbalanced-learn, and scikit-surprise and use it to solve real-world machine learning problemsstrongppstrongKey Featuresstrongp ul liDelve into machine learning with this comprehensive guide to scikit-learn and scientific Pythonli liMaster the art of data-driven problem-solving with hands-on examplesli liFoster your theoretical and practical knowledge of supervised and unsupervised machine learning algorithmsli ul pstrongBook Descriptionstrongp pMachine learning is applied everywhere, from business to research and academia, while scikit-learn is a versatile library that is popular among machine learning practitioners. This book serves as a practical guide for anyone looking to provide hands-on machine learning solutions with scikit-learn and Python toolkits.p pThe book begins with an explanation of machine learning concepts and fundamentals, and strikes a balance between theoretical concepts and their applications.