15+ Machine/Deep Learning Projects in Ipython Notebooks

دوره جامع یادگیری عمیق با Tensorflow و Keras

Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.

Jupyter Notebook for Human Activity Recognition (HAR) with 1D Convolutional Neural Network in Python and Keras

TensorFlow 2.X hakkında (Türkçe) öğretici notebooklar paylaşıyorum. Repoyu yararlı bulursanız yıldızlayarak destek olabilirsiniz :)

Machine Learning Engineer Nanodegree portfolio, which includes projects and their notebooks/reports.

Exporting the Mask RCNN with TF-Serving (REST, GRPC, Notebooks provided)

Bird Classifier developped in tensorflow using pre-trained model from Tensorflow Hub and running on Google Colab

Some useful examples of Deep Learning (.ipynb)

A collection of deep learning notebooks.

Notebooks for colab that use the TPU

exploring new tensorflow 2.0 API

This repository contains the jupyter notebooks for the custom-built DenseNet Model build on Tiny ImageNet dataset

This repository contains the Jupyter Notebook for the InceptionV3 CNN Model trained on the Stanford Dogs Dataset.

iPython notebook for training a Keras model on the CIFAR-10 dataset

I have built the computer vision models in 3 different ways addressing different personas, because not all companies will have a resolute data science team. quality-control manufacturing big-data-analytics jupyter-notebook cognitive services industry solutions

The repository contains the Jupyter Notebook that perform semantic segmentation using the famous U-Net. The encoder of the U-Net is replaced with the pretrained encoder.

This is a repository with various classifier written in jupyter notebook that works on hand written digits images.

This repository contains the jupytor notebook code for digit recognition using machine learning.

Jupyter notebooks for practicing Python data analysis and visualization with Matplotlib, NumPy, Pandas, SciPy, Seaborn, Keras, TensorFlow, and PyTorch.