Machine-Learning-Specialization-Coursera
cs229-2018-autumn
Machine-Learning-Specialization-Coursera | cs229-2018-autumn | |
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6 | 112 | |
2,728 | 1,394 | |
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4.1 | 3.5 | |
7 days ago | 20 days ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | - |
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Machine-Learning-Specialization-Coursera
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Linear Algebra for Programmers
I cannot recommend Andrew Ng's courses on Machine Learning enough. Something like this seems like it would cover everything you're looking for.
https://www.coursera.org/learn/machine-learning
I cannot speak to the author of the content of this github repo, but it appears they have completed the course and included all of the solutions here. It might let you jump right to what you're looking for.
https://github.com/greyhatguy007/Machine-Learning-Specializa...
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Stupid question but help with Andrew Ng course
github link : GitHub - greyhatguy007/Machine-Learning-Specialization-Coursera: Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
- Machine Learning Specialization
- Alternatives to Andrew Ng's Machine Learning course on Coursera
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Is there no way to do the labs exercises on Coursera unless I pay for it?
Found this and it may have some of the labs https://github.com/greyhatguy007/Machine-Learning-Specialization-Coursera
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I'm a highly motivated undergrad from a 3rd world country who is unable to afford the paid version of new Andrew NG course. What can I do about the labs?
https://github.com/greyhatguy007/Machine-Learning-Specialization-Coursera This guy has added all the quizzes and labs of this course.
cs229-2018-autumn
- cs229-2018-autumn: NEW Courses - star count:949.0
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Mathematics courses for machine learning/deep learning.
Definitely check out CS229: https://cs229.stanford.edu/
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Are there any books I should read to learn machine learning from scratch?
For machine learning (not deep learning), I recommend the lecture notes from Stanford's CS229 course. The reason I really like these notes is because you can find past problem sets that went along with them, and the problem sets are very good: difficult but not impossible, and close to a 50/50 mix of math and programming. I never feel like I've learned a topic just from reading about it, so having good problems to go along with the reading was very important to me.
- cs229-2018-autumn: NEW Courses - star count:834.0
What are some alternatives?
Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions - Solutions of Reinforcement Learning, An Introduction
cs229-2019-summer - All notes and materials for the CS229: Machine Learning course by Stanford University
Spotify_Song_Recommender - This project leverages spotify's api and provided user playlists to create and tune a neural network model that generates song recommendations based off of song data in provided playlists.
stanford-CS229 - Python solutions to the problem sets of Stanford's graduate course on Machine Learning, taught by Prof. Andrew Ng [UnavailableForLegalReasons - Repository access blocked]
coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
stanford-cs229 - 🤖 Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford
Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera - Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
probability - Probabilistic reasoning and statistical analysis in TensorFlow
handson-ml - ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Car-Price-Prediction - A machine learning project that predicts the price of used cars in the UK
huggingface_hub - The official Python client for the Huggingface Hub.