Hacktoberfest encourages participation in the open source community, which grow
- Just Choosse any easy app or website to clone
- Upload the coded file in correct folder with correct way
- You can use Google, Youtube or any other open source
1. Fork this repo
2. Star this repo
3. Add a file
4. commit the code
5. Make pull request
Convolutional Neural Network (CNN) is an algorithm taking an image as input then assigning weights and biases to all the aspects of an image and thus differentiates one from the other. Neural networks can be trained by using batches of images, each of them having a label to identify the real nature of the image (cat or dog here). A batch can contain few tenths to hundreds of images. For each and every image, the network prediction is compared with the corresponding existing label, and the distance between network prediction and the truth is evaluated for the whole batch. Then, the network parameters are modified to minimize the distance and thus the prediction capability of the network is increased. The training process continues for every batch similarly.
- Firstly create a new python 3.7 Environment by using the command
conda create -n myenv python=3.7 - Secondly Activate the environment by using command
conda activate myenv - Thirdly Activate python runtime by using
python. - Then run a requirements.txt file by using command
pip install -r requirements.txt - Afterwards run the App.py file using command
python clientApp.py.