| PatWie/CppNumericalSolvers |
766 |
|
0 |
0 |
over 3 years ago |
0 |
|
2 |
mit |
C++ |
| a lightweight C++17 library of numerical optimization methods for nonlinear functions (Including L-BFGS-B for TensorFlow) |
| mattnedrich/GradientDescentExample |
428 |
|
0 |
0 |
over 6 years ago |
0 |
|
1 |
mit |
Python |
| Example demonstrating how gradient descent may be used to solve a linear regression problem |
| gokadin/ai-simplest-network |
317 |
|
0 |
0 |
almost 6 years ago |
0 |
|
0 |
|
Go |
| The simplest form of an artificial neural network explained and demonstrated. |
| javascript-machine-learning/organization-overview |
310 |
|
0 |
0 |
almost 6 years ago |
0 |
|
0 |
|
|
| 👇 Overview of all the resources of BRIIM: JavaScript in Machine Learning |
| dilinwang820/Stein-Variational-Gradient-Descent |
261 |
|
0 |
0 |
about 7 years ago |
0 |
|
1 |
mit |
Python |
| code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm" |
| sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python |
241 |
|
0 |
0 |
over 5 years ago |
0 |
|
1 |
|
Jupyter Notebook |
| Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow |
| mstksg/backprop |
180 |
|
18 |
0 |
over 2 years ago |
23 |
July 23, 2023 |
4 |
bsd-3-clause |
Haskell |
| Heterogeneous automatic differentiation ("backpropagation") in Haskell |
| faridcher/ml-course |
168 |
|
0 |
0 |
about 2 years ago |
0 |
|
0 |
|
R |
| Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language |
| llSourcell/Intro_to_the_Math_of_intelligence |
153 |
|
0 |
0 |
almost 7 years ago |
0 |
|
2 |
mit |
Python |
| This is the code for "Intro - The Math of Intelligence" by Siraj Raval on Youtube |
| lucfra/FAR-HO |
133 |
|
0 |
0 |
about 6 years ago |
0 |
|
2 |
mit |
Jupyter Notebook |
| Gradient based hyperparameter optimization & meta-learning package for TensorFlow |
