maximum likelihood estimate #maths #datascience #machinelearning #mathematics
Key Takeaways
This video teaches the maximum likelihood estimate in machine learning and mathematics
Original Description
📚 *RECOMMENDED BOOKS TO START WITH MACHINE LEARNING*
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If you're new to ML, here are the 3 best books I recommend (I've personally read all of these):
1. Hands-On Machine Learning – the go-to practical ML guide: https://amzn.to/3UcGqSS
2. Mathematics for Machine Learning – deep dive into the theoretical aspects of ML: https://amzn.to/3IZgHe7
3. Designing Machine Learning Systems - practical strategies for building scalable ML solutions: https://amzn.to/4ojEqFX
These are affiliate links, so buying through them helps support the channel at no extra cost to you — thanks 🙏
*Summary*
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This video explains Maximum Likelihood and Maximum Likelihood Estimation (MLE) with clear intuition. Learn how maximum likelihood works, why it is used in statistics and machine learning, and how parameters are estimated by maximizing the likelihood of observed data. This introduction to MLE covers the core idea behind likelihood functions, parameter estimation, probability models, and statistical inference used in data science, AI, and machine learning.
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