This week you'll learn best practices for training and evaluating your learning algorithms to improve performance. This will cover a wide range of useful advice about the machine learning lifecycle, tuning your model, and also improving your training data.

In a world where data-driven solutions are revolutionizing industries, mastering advanced machine learning techniques is a pivotal skill that empowers innovation and strategic decision-making. This equips you with the expertise needed to harness advanced machine-learning algorithms.

Gain expertise in machine learning with advanced algorithms, model tuning, and real-world applications.

a) understand the naïve Bayesian algorithm. b) understand the Support Vector Machine algorithm. c) understand the Decision Tree algorithm. d) understand the Clustering. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability.

Dec 20, 2024 · Machine learning: Dive into the various types of machine learning algorithms, such as supervised, unsupervised, and reinforcement learning. Deep learning: Understand neural networks and the concepts of deep learning. Month 7-9: …

Jan 28, 2025 · In this article, you'll learn about 10 of the most popular machine learning algorithms used to complete tasks today, their different uses, and how they apply to different types of machine learning.

Jan 13, 2025 · Learn machine learning for financial engineering applications with Coursera. Machine learning and finance often work together, and you can find a role within the financial field that uses machine learning skills.

Machine learning courses focus more specifically on algorithms that learn from data. Many learners find it beneficial to start with machine learning before moving to broader AI topics. ‎

Jan 19, 2018 · Acquire knowledge of different algorithms and learn how to efficiently tune their hyperparameters and achieve top performance. Master the art of combining different machine learning models and learn how to ensemble. Get exposed to past (winning) solutions and codes and learn how to read them.

You will implement machine learning models using Python and will learn about the many applications of machine learning used in industry today. You will also learn about and use different machine learning algorithms to create your models.