How to find the best model parameters in scikit learn

Machine learning in python, in this course we will learn about machine learning in Python, covering both theory and practical implementation. We will explore supervised and unsupervised learning, classification, regression, clustering, and dimensionality reduction using powerful Python libraries such as scikit-learn, pandas, NumPy, and Matplotlib. You will gain hands-on experience in preparing datasets, training models, evaluating performance, and improving accuracy using techniques like cross-validation and hyperparameter tuning. Whether you are predicting outcomes, discovering patterns, or building smart applications, this course will guide you through the core concepts and help you apply them effectively. By the end, you'll be able to build machine learning models from scratch, interpret their outputs, and deploy your solutions confidently in real-world scenarios. No prior ML experience needed—just basic Python knowledge. Data School