areflesh
Thorough and meticulous Data Analyst passionate about helping businesses succeed and academic researches. Recipient of a Master in Data science.
Pinned Repositories
API
BayesianNetworks
Examples of code on R in solving different problems using Bayesing Networks.
data_annotator
data_annotator_heroku
fake_news
images
Machine-Learning-Project
Human activity recognition is one of the interesting spheres for machine learning. We can measure human activity by several methods and then try suggest right decisions about conditions of health of person. Smartphones help us to provide all necessary information for making such kind of models. This project is about using randomForests and SVA algorithms in making decision models and comparison of this algorithms.
Mask_RCNN_blur
Mathematical-Modelling-
Research porject "Reconstruction of hidden part of shape on picture using methods of mathematical modelling and machine learning" of course of Mathematical Modelling
pose_es
areflesh's Repositories
areflesh/fake_news
areflesh/radarai
areflesh/streamlit-example
Example Streamlit app that you can fork to test out share.streamlit.io
areflesh/images
areflesh/data_annotator_heroku
areflesh/data_annotator
areflesh/res
areflesh/API
areflesh/SGOAB_v2
areflesh/pose_es
areflesh/TM_seminar
areflesh/Mask_RCNN_blur
areflesh/sgoab_dataset
areflesh/stylegan
areflesh/Machine-Learning-Project
Human activity recognition is one of the interesting spheres for machine learning. We can measure human activity by several methods and then try suggest right decisions about conditions of health of person. Smartphones help us to provide all necessary information for making such kind of models. This project is about using randomForests and SVA algorithms in making decision models and comparison of this algorithms.
areflesh/Mathematical-Modelling-
Research porject "Reconstruction of hidden part of shape on picture using methods of mathematical modelling and machine learning" of course of Mathematical Modelling
areflesh/BayesianNetworks
Examples of code on R in solving different problems using Bayesing Networks.