Machine-Learning-Specialization-Coursera
Car-Price-Prediction
| Machine-Learning-Specialization-Coursera | Car-Price-Prediction | |
|---|---|---|
| 6 | 1 | |
| 2,704 | 11 | |
| - | - | |
| 4.1 | 0.0 | |
| 14 days ago | about 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | 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.
Car-Price-Prediction
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ValueError: Input contains NaN, infinity or a value too large for dtype('float64').
I am doing over this tutorial but with my data which is not about cars so I skipped the part about categorical labels... https://github.com/VictorUmunna/Car-Price-Prediction/blob/master/model_building.ipynb
What are some alternatives?
Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions - Solutions of Reinforcement Learning, An Introduction
F1_Quali_Prediction - Finding explainable models to predict Formula 1 Qualifying Results
cs229-2018-autumn - All notes and materials for the CS229: Machine Learning course by Stanford University
100DaysofMLCode - My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
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.
cliodynamics - This repository tries to analyze history from a computer science perspective.
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
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera - Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
handson-ml - ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
machine_learning_basics - Plain python implementations of basic machine learning algorithms