Published on: 2024-10-14 04:10:58
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Math 0-1: Probability for Data Science & Machine Learning is a training course on probability for data science and machine learning published by the online academy of Udemy. Math 0-1: Probability for Data Science & Machine Learning is a specialized course designed to provide a solid foundation in probability theory, with a focus on its applications in data science and machine learning. This course covers basic concepts such as random variables, probability distributions, conditional probability, Bayes theorem and the law of large numbers. Learners will also explore topics such as joint and marginal distributions, expectations, variance, and probability in the context of algorithms, including supervised and unsupervised learning. Through hands-on exercises, students apply probability theory to real-world problems in data science, such as forecasting, managing uncertainty, and optimizing models.
This course covers random variables, probability distributions, conditional probability, and Bayes theorem, focusing on their applications in data science. Learners will examine joint distributions, expectations, and variances and apply these concepts to algorithms and model optimization in machine learning. Through practical exercises, they will gain a deeper understanding of the role of probability in forecasting and managing uncertainty. At the end of the course, learners will have a strong understanding of probability and its practical application in machine learning and data-driven decision making.
College / University-level Calculus (for most parts of the course)
College / University-level Linear Algebra (for some parts of the course)
After Extract, watch with your favorite Player.
Subtitle: English
Quality: 720p
Changes:
Version 2024/10 compared to 2024/9 has increased the number of 21 lessons and the duration of 4 hours and 1 minutes. English subtitles have also been added to the course.
9.49 GB
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