smasis001/ddd-estimator-opencv smasis001/ddd-estimator-opencv

  • Stars
    star
    24
  • Rank 986,245 (Top 20 %)
  • Language
    Jupyter Notebook
  • License
    GNU Lesser Genera...
  • Created almost 6 years ago
  • Updated almost 6 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
smasis001/ddd-estimator-opencv
github

smasis001

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Driver Alertness Detection using Ensemble of Regression Trees and Implemented in OpenCV

More Repositories

1

dsdojo-2022

Workshop for Data Science Dojo September 2022
Jupyter Notebook
11
star
2

odsc-west-2022

Workshop for Open Data Science Conference East 2022
Jupyter Notebook
9
star
3

av-2022

Workshop for Analytics Vidhya July 2022
Jupyter Notebook
6
star
4

ml-prague-2021

Presentation for Machine Learning Prague 2021
Jupyter Notebook
5
star
5

pydata-2020

Workshop for PyData 2020
Jupyter Notebook
5
star
6

odsc-west-2020

Workshop for Open Data Science Conference West 2020
Jupyter Notebook
4
star
7

datacamp2022

Workshop for DataCamp July 2022
Jupyter Notebook
4
star
8

dsgo-virtual-2021

DataScienceGo Virtual April 2021 Workshop
Jupyter Notebook
3
star
9

Facial-Recognition-App

Facial Recognition App with Python Backend and JS Frontend
Python
3
star
10

odsc-east-2022

Workshop for Open Data Science Conference East 2022
Jupyter Notebook
3
star
11

smart-grid-peak-tariff-optimization

Smart Grid Peak Tariff Optimization with Reinforcement Learning
Jupyter Notebook
2
star
12

dphi-2021

Jupyter Notebook
2
star
13

Music-GenAI-App

Music Generation with AI App
Python
1
star
14

mlconf-2023

Workshop for ML Conference Berlin 2022
Jupyter Notebook
1
star
15

ml-summit-2021

Workshop for ML Summit April 2021
Jupyter Notebook
1
star
16

aisc-2021

Presentation for Aggregate Intellect, March 2021
Jupyter Notebook
1
star
17

datatalks-2022

Jupyter Notebook
1
star
18

Machine-Learning-Datasets

A simple library for loading machine learning datasets and performing some common machine learning interpretation functions. Built for the book "Interpretable Machine Learning with Python".
Python
1
star