Course link: https://aicourse.thinkific.com/courses/python-machine-learning-crash-course-for-beginners
In this video, we take a deep dive into building a machine learning model from scratch using Python, focusing on linear regression. Instead of relying on built-in tools like Scikit-Learn, we explain and implement the entire process manually to give you a clear, hands-on understanding of how machine learning works under the hood. Starting with the mathematical foundations of linear regression, we walk through the concept of mapping features to targets, matrix representation, and the use of least squares optimization to find the best-fit line. Then, we transition into coding the model in Jupyter Notebook using NumPy, where we generate synthetic data, account for noise, and compute predictions using our own implementation. This beginner-friendly tutorial is part of the “Building Machine Learning Model from Scratch” module in the “Python Machine Learning Crash Course for Beginners” and is designed to help you gain confidence in both the theory and practice of machine learning.
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We decided to produce courses and books mainly dedicated to beginners and newcomers on the techniques and methods of machine learning, statistics, artificial intelligence, and data science. Initially, our objective was to help only those who wish to understand these techniques more easily and to be able to start with less theory or lengthy reading. Today, we publish more complete books on selected topics for a wider audience.
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