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Get ready to put on your detective hats because this is where things get really interesting! This module is all about **machine learning fundamentals**. We'll introduce the core concepts of machine learning, explore different types of machine learning algorithms, and start building your own models. We'll start by talking about the concept of machine learning, the differences between supervised, unsupervised, and reinforcement learning, and the machine learning workflow. Next, we'll go over the supervised learning algorithms, such as linear regression, logistic regression, and support vector machines (SVMs). You will understand what each of these algorithms does, and you'll learn how to implement them. After this, we will move on to the unsupervised learning algorithms, such as clustering algorithms (k-means) and dimensionality reduction techniques (PCA). You will learn how to implement them to find hidden patterns. You will then get into the topic of model evaluation, which is about understanding how to measure the performance of your machine-learning model. This involves concepts like accuracy, precision, recall, and the F1-score. This module will give you a solid foundation in the most important machine learning algorithms. You'll gain a thorough understanding of how these algorithms work. After this module, you will be able to implement machine learning models from scratch, which will enable you to solve the practical AI problems. By the end of this module, you'll be able to understand the core concepts of machine learning. You'll gain experience in implementing and evaluating your own machine-learning models.
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3. **Read the Installation Instructions:** Each mod will have its own installation instructions. Pay close attention to these instructions, as they can vary depending on the mod. Most mods come with a readme file that guides you through the process.
