Advanced Machine Learning with Python

Welcome to "Advanced Machine Learning with Python," a comprehensive course designed to equip you with the advanced knowledge and skills needed to excel in machine learning. Throughout this program, you will explore various advanced machine learning concepts, algorithms, and practical applications.

This course covers crucial topics, including feature selection, data preprocessing, bagging and boosting techniques, and model tuning with grid search. You will also delve into specific algorithms such as linear regression, random forest, and Naive Bayes theorem, gaining hands-on experience with Python to build and optimize machine learning models.

What Will Students Learn in This Course?

• Feature Selection: Gain a solid understanding of feature selection techniques to improve model performance by selecting the most relevant features.

• Data Preprocessing: Learn advanced data preprocessing methods, including handling missing values, scaling, and normalization.

• Bagging and Boosting: Explore ensemble learning techniques such as bagging and boosting to enhance model accuracy and robustness.

• Model Tuning and Grid Search: Understand the process of model tuning using grid search to find the optimal hyperparameters for your models.

• Linear Regression: Dive deep into linear regression, understanding its principles and applications.