Name: Cristian Daniel Alecsa
Type: User
Company: PhD in Mathematics
Bio: Applied Mathematics; Statistics; Machine Learning / Data Science; Scientific Computing
Location: Romania
Blog: https://scholar.google.ro/citations?user=394mWmgAAAAJ&hl=ro
aammsu
- implementations in PyTorch regarding AAMMSU optimizer
boundary-value-problem-2d
finite difference method for a two-dimensional Poisson BVP with nonconstant spatial coefficients
computational-statistics
Monte Carlo based methods for the approximation of given functions. The approximation of PI is also included
deep-neural-networks-in-keras
- DNN in Keras for Fashion MNIST dataset, including learning rate with decay rate, comparison for dropouts, image prediction, loss and accuracy plots
dnn-for-mnist-dataset
- DNN from scratch in Python, including different optimizers, cost functions and activation functions
finite-difference-methods---oop
some basic object oriented programming codes made in Python for the comparison between backward ( implicit ) Euler method and the analytical solution of an IVP
function-approximation-by-neural-networks---1d-case
- this repository contains some one-dimensional function approximations by neural networks
generalized-kmm
a generalized version of KMM involving multiple train and test datasets
linear-regression-in-sklearn
- includes multi-linear regression on a complete set of features, linear regression made independently on each relevant feature, correlation matrix and feature distributions
multioutput-stratified-splitting
This method provides train/test indices according to multiple target columns, and it is suitable for applications involving multiclass-multioutput classification tasks.
oblique-forest-autoencoders
an autoencoder method constructed using ensembles of oblique decision trees
optimization-algorithms-i
a comparison of various optimization algorithms using different objective functions
optimization-algorithms-ii
a comparison of Polyak and Nesterov classical algorithms using convex / nonconvex higher dimensional mappings
optimization-algorithms-iii
- different type of optimizers for 1D and 2D objective functions. A comparison using the energy dissipation, phase portrait, decrease in the objective function.
statistics-and-prediction-in-python
- descriptive statistics and prediction, using different techniques in Python
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
Django
The Web framework for perfectionists with deadlines.
Laravel
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
Microsoft
Open source projects and samples from Microsoft.
Google
Google ❤️ Open Source for everyone.
Alibaba
Alibaba Open Source for everyone
D3
Data-Driven Documents codes.
Tencent
China tencent open source team.
