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Name: Filip M
Type: User
Bio: ML engineer with background in Mechatronics with an inborn curiosity and pursuit of ambitious challenges.
Name: Filip M
Type: User
Bio: ML engineer with background in Mechatronics with an inborn curiosity and pursuit of ambitious challenges.
An application to automatically remove selected objects from images and videos
Implementation of DNN algorithm with using only the numpy library. Model is trained using batch gradient descent and tested on MNIST dataset achieving 94% accuracy on test set. Dropout and L2 are implemented as regularization algorithms. Optimizer can be chosen between gradient descent and Adam. The model is fully scallable, which means that regularization parameter as well as numbers of hidden layers and nodes can be set to any value. All functions, including forward propagation, back propagation, cross entropy loss calculation, dropout and training algorithm are written without the tensorflow library. Different activation function can be used: sigmoid, Relu or hyperbolic tangent.
A Keras implementation of YOLOv3 (Tensorflow backend)
The following program applied k-means algorithm for unsupervised learning with sklearn circles dataset. To create a decision boundary in the case of non-linear dataset, Gaussian kernels are utilized. In order to make the model computationally less expensive, dimensions reduction using principal component analysis was applied. All functions, including model building and trainins, kernels calculation and dimensions reduction were written from scratch without using any built-in sklearn functions.
Segmentation for land cover using raw satellite data (Sentinel 2La)
Land cover tracking Web App
The program has two main functionalities. The first one is building a regularized recommender system with collaborative filtering and learning it with a "MovieLens" dataset (https://grouplens.org/datasets/movielens/) with 1 millions movie ratings. The second feature is finding recommendations for a new user, which is done by implementation of a content-based recommender system. A user, after inputting some ratings to the "Movies_fornewuser.txt" file, can use provided model, which was learnt using the first feature, to find new movies recommendations. In order to use, please read README.md.
Case study for semi-supervised learning using imbalanced CIFAR 1- dataset
A sentiment analysis model trained on Amazon reviews dataset.
The project includes two solutions for a traffic signs recognition. Original dataset is available at https://www.kaggle.com/valentynsichkar/traffic-signs-preprocessed. The first solution utilizes tensorflow framework to build a scalable Deep Neural Network to recognize 43 different traffic signs. Its accuracy with the cross validation set reaches 90%. Algorithm implements batch normalization, learning rate decay and dropout. For cost function minimization it uses minibatch Adam optimizer. In the second solution, convolutional layers are used and a model based on VGG-16 architecture is built. Its accuracy with the cross validation set reaches 95%. Algorithm implements batch normalization, learning rate decay and dropout. For cost function minimization it uses minibatch Adam optimizer.
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 is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
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.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.