Concise and beautiful algorithms written in Julia

Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|

Cs Video Courses | 56,273 | 8 days ago | 17 | |||||||

List of Computer Science courses with video lectures. | ||||||||||

C Plus Plus | 24,605 | a day ago | 32 | mit | C++ | |||||

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes. | ||||||||||

Homemade Machine Learning | 21,220 | a month ago | 22 | mit | Jupyter Notebook | |||||

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained | ||||||||||

Wavefunctioncollapse | 20,815 | 3 months ago | 2 | other | C# | |||||

Bitmap & tilemap generation from a single example with the help of ideas from quantum mechanics | ||||||||||

C | 16,319 | a day ago | 16 | gpl-3.0 | C | |||||

Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes. | ||||||||||

Recommenders | 15,822 | 2 | 19 hours ago | 11 | April 01, 2022 | 164 | mit | Python | ||

Best Practices on Recommendation Systems | ||||||||||

Nni | 12,968 | 8 | 22 | 3 days ago | 51 | June 22, 2022 | 284 | mit | Python | |

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. | ||||||||||

Machine Learning Tutorials | 12,876 | 5 months ago | 33 | cc0-1.0 | ||||||

machine learning and deep learning tutorials, articles and other resources | ||||||||||

Halfrost Field | 11,971 | 2 months ago | 6 | cc-by-sa-4.0 | Go | |||||

✍🏻 这里是写博客的地方 —— Halfrost-Field 冰霜之地 | ||||||||||

Numerical Linear Algebra | 9,325 | 2 months ago | 11 | Jupyter Notebook | ||||||

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course |

Alternatives To Beautifulalgorithms.jlSelect To Compare

Alternative Project Comparisons

Readme

Concise algorithms written in Julia and formatted with Carbon.

Algorithms for machine learning, optimization, reinforcement learning, online planning, decision making under uncertainty, and sorting. All implementations are working and self-contained; refer to the test cases.

Note, these are primarily for academic purposes and are not designed for real-world usage. There are many other Julia packages that implement more sound versons of these algorithms.

```
] add http://github.com/mossr/BeautifulAlgorithms.jl
```

- Gradient descent
- Stochastic gradient descent
- Two-layer neural network
- Multi-layer neural network
- Loss functions
- Distance functions
- Nearest neighbor
- K-nearest neighbors
- K-means clustering
- The EM algorithm
- Linear regression
- Ridge regression
- Basis regression
- Radial basis regression
- Logistic regression
- Cross-entropy method
- Finite difference methods
- Simulated annealing
- Twiddle
- Newton's method
- Gaussian process
- Thompson sampling
- Particle filter
- Value iteration
- Branch and bound
- Monte Carlo tree search
- Huffman coding
- Hailstone sequence (Collatz conjecture)
- Bubble sort
- Merge sort
- Insertion sort
- Bogo sort
- Quine

*Note: Algorithms are modified from their original sources.*

Percy Liang and Dorsa Sadigh, *Artificial Intelligence: Principles and Techniques*, Stanford University, 2019.

Percy Liang and Dorsa Sadigh, *Artificial Intelligence: Principles and Techniques*, Stanford University, 2019.

Percy Liang and Dorsa Sadigh, *Artificial Intelligence: Principles and Techniques*, Stanford University, 2019.

Andrew Ng, *Mixtures of Gaussians and the EM algorithm*, Stanford University, 2020.^{1}

Mykel J. Kochenderfer and Tim A. Wheeler, *Algorithms for Optimization*, MIT Press, 2019. (Credit @HenriDeh for use of `ones`

)

Mykel J. Kochenderfer and Tim A. Wheeler, *Algorithms for Optimization*, MIT Press, 2019.

Mykel J. Kochenderfer and Tim A. Wheeler, *Algorithms for Optimization*, MIT Press, 2019.

Mykel J. Kochenderfer and Tim A. Wheeler, *Algorithms for Optimization*, MIT Press, 2019.

Mykel J. Kochenderfer and Tim A. Wheeler, *Algorithms for Optimization*, MIT Press, 2019.

Mykel J. Kochenderfer and Tim A. Wheeler, *Algorithms for Optimization*, MIT Press, 2019.

Sebatian Thrun, *Artificial Intelligence for Robotics*, Udacity, 2012.

John Wallis, *A Treatise of Algebra both Historical and Practical*, 1685.

Mykel J. Kochenderfer and Tim A. Wheeler, *Algorithms for Optimization*, MIT Press, 2019.

Daniel J. Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband, and Zheng Wen, *A Tutorial on Thompson Sampling*, arXiv:1707.02038, 2020.

Mykel J. Kochenderfer, Tim A. Wheeler, and Kyle H. Wray, *Algorithms for Decision Making*, Preprint.

Mykel J. Kochenderfer, Tim A. Wheeler, and Kyle H. Wray, *Algorithms for Decision Making*, Preprint.

Mykel J. Kochenderfer, Tim A. Wheeler, and Kyle H. Wray, *Algorithms for Decision Making*, Preprint.

Mykel J. Kochenderfer, Tim A. Wheeler, and Kyle H. Wray, *Algorithms for Decision Making*, Preprint.

David A. Huffman, *A Method for the Construction of Minimum-Redundancy Codes*, IEEE, 1952.

Karey Shi, *Design and Analysis of Algorithms*, Stanford University, 2020.

Karey Shi, *Design and Analysis of Algorithms*, Stanford University, 2020.

Karey Shi, *Design and Analysis of Algorithms*, Stanford University, 2020.

Nathan Daly, *Julia Discord*, 2019.^{2}

Written by Robert Moss.

Popular Algorithms Projects

Popular Machine Learning Projects

Popular Computer Science Categories

Related Searches

Get A Weekly Email With Trending Projects For These Categories

No Spam. Unsubscribe easily at any time.

Machine Learning

Algorithms

Neural Network

Julia

Optimization

Reinforcement Learning