ฝัง
- เผยแพร่เมื่อ 14 พ.ย. 2024
- Sigmoid Tech Talk - a video series on emerging data and analytics topics.
Welcome to the episode 7 of Sigmoid Tech Talk - "Gradient Descent Explained"! Join us as Ankit Sharma, Associate Lead Data Scientist at Sigmoid, takes you on a journey through the intricacies of one of the fundamental optimization algorithms in machine learning.
🔥 Part 1: Embark on your exploration with Ankit Sharma in the first installment of our series. In this segment, Ankit elucidates Linear Regression - its significance, advantages, and real-world applications. Prepare to delve into the formulas that underlie the calculation of linear regression, gaining a solid foundation for what's to come.
🚀 Part 2: The journey continues in the second part of our "Gradient Descent" series. Ankit Sharma unravels the mysteries of the Convergence Theorem and its practical implementation in the context of gradient descent. Discover how this theorem plays a pivotal role in deriving optimal linear solutions.
🌟 Part 3: As we reach the final chapter of this enlightening series, Ankit leads you through the impact of the learning rate on linear regression solutions. Uncover the nuances of different gradient descent techniques and gain insight into their pros and cons, helping you navigate the world of optimization.
Whether you're an aspiring data scientist or someone curious about the inner workings of gradient descent, this three-part series is tailor-made for you. Enhance your understanding of linear regression, optimization, and the art of finding optimal solutions. Hit that play button and embark on your journey of knowledge with us!
