Lung registration full functional job

Sentiment Analysis by using Tensorflow dataset Yelp-Restaurant-Review

Deformable lung image registration with a Dice score over 0.9 with only 10 Epochs

Data generation with using DCGAN

Various Machine Learning model Experiment with Tesnorflow Iris Dataset

Brain tumor classification

Single click distributed training using pytorch

Single click distributed training using Tensorflow

Udacity - Deep Learning - Part 4 -Classifying Fashion-MNIST in pytorch

Udacity Deep Learning - Pytorch - Part 3 - Training Neural Networks in Pytorch

Udacity Deep Learning - Pytorch - Part 2 Neural Networks in Pytorch

Udacity Deep Learning Nano Degree - Pytorch - Part 1 - Intro to Tensors in pytorch

In this notebook we will train a scikit-learn and a cuML Random Forest Classification model. Then we save the cuML model for future use with Python's pickling mechanism and demonstrate how to re-load it for prediction. We also compare the results of the scikit-learn, non-pickled and pickled cuML models.

This Project does a custom object detection using YOLO model. The trained model was used to develop a tracking algorithm.

This book is a unique walk through for all aspirants that look forward to grasp the idea of supervised learning from scratch. This book shows the use of various metrics and hyper parameter tuning. Also this book sheds light into application of classifiers like KNN and so on... Happy learning....

This notebook is a basic operational procedure of statistical understanding of data and associated operations using numpy and pandas. Would be a great help for beginners to better understand the concepts in detail

The project is a simple elaboration of the concept of object detection from the tensorflow website.

This project represents a computer vision problem and solution with respect to activity recognition. The presented notebook is an example of a successfully compiled one that was able to identify activities from the predefined activities on recorded videos. The dataset used for the learning was UCF 50. All the methods including downloading and utilising the dataset is elaborated in the code base.

This Project does a custom object detection using YOLO model. The trained model was used to develop a tracking algorithm.

Built in MLFlow integration

Tensorflow MultiNode training

Tensorflow distributed training on multiple nodes

Built in Tensorboard Viewer

Convnext

Q&A with pytorch

Vtoonify in action