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Looking for Study Buddy for Stanford CS229 Machine Learning (Andrew Ng, Autumn 2018)
16th July, 2024
Last date to join: 31st July, 2024
Hey I'm starting the Stanford CS229 Machine Learning course by Andrew Ng (the Autumn 2018 version). It's available as a full playlist on YouTube. I'm looking for a study buddy or a small group to go through the material together. I think having someone to discuss the lectures, assignments, and concepts with would be incredibly helpful. About Me: Background: I have a basic understanding of programming and math (calculus, linear algebra, and some probability). Goals: I want to solidify my understanding of ML fundamentals and build a strong foundation for further learning. Time Zone: GMT+3 What I'm Looking For in a Study Buddy: Similar background and goals. Commitment to sticking with the course schedule. Enthusiasm for learning and discussing ML. If you're interested, please DM me
UTC+03.00
Novice
English
Description
This course provides an introduction to the field of machine learning, covering basic models such as linear regression and logistic regression, as well as more advanced techniques such as support vector machines (SVMs) and neural networks. Topics also include decision trees, ensemble methods, expectation-maximization algorithms, independent component analysis, reinforcement learning and linear dynamical systems. It also covers topics such as data splits, model selection and cross-validation, debugging, and diagnostics. Finally, the lectures further explore the fundamentals of machine learning, such as gradient descent, moments, and optimization, in order to lay the foundations for advanced machine learning topics.
Stanford CS229 - Machine Learning Full Course Taught by Andrew Ng - Autumn 2018
Online Courses 
YouTube
Free 
1 day 3 hours Get notified about new study groups every week!
Looking for Study Buddy for Stanford CS229 Machine Learning (Andrew Ng, Autumn 2018)
16th July, 2024
Last date to join: 31st July, 2024
Affiliate notice
Hey I'm starting the Stanford CS229 Machine Learning course by Andrew Ng (the Autumn 2018 version). It's available as a full playlist on YouTube. I'm looking for a study buddy or a small group to go through the material together. I think having someone to discuss the lectures, assignments, and concepts with would be incredibly helpful. About Me: Background: I have a basic understanding of programming and math (calculus, linear algebra, and some probability). Goals: I want to solidify my understanding of ML fundamentals and build a strong foundation for further learning. Time Zone: GMT+3 What I'm Looking For in a Study Buddy: Similar background and goals. Commitment to sticking with the course schedule. Enthusiasm for learning and discussing ML. If you're interested, please DM me
UTC+03.00
Novice
English
-
TypeOnline Courses
-
ProviderYouTube
-
PricingFree
-
Duration1 day 3 hours
This course provides an introduction to the field of machine learning, covering basic models such as linear regression and logistic regression, as well as more advanced techniques such as support vector machines (SVMs) and neural networks. Topics also include decision trees, ensemble methods, expectation-maximization algorithms, independent component analysis, reinforcement learning and linear dynamical systems. It also covers topics such as data splits, model selection and cross-validation, debugging, and diagnostics. Finally, the lectures further explore the fundamentals of machine learning, such as gradient descent, moments, and optimization, in order to lay the foundations for advanced machine learning topics.
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31st July, 2024
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