stefannatu

amazon-a2i-sample-jupyter-notebooks

Sample Jupyter Notebooks for Amazon Augmented AI (A2I)

amazon-forecast-samples

Notebooks and examples on how to onboard and use various features of Amazon Forecast.

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

amazon-sagemaker-studio-vpc-blog

Diffusion-Limited-Aggregation

2D Simulation modeling clustering of particles undergoing Brownian motion.

Handling-large-imbalanced-data

Explore training large ML models at scale using Tensorflow APIs, sharding data, handling imbalanced data by training for precision/recall over accuracy

NLP-Translation-Models

Experimenting with different architectures for neural machine translation

Semantic-Segmentation

Udacity Course -implement FCN for image segmentation

Sequence-to-Sequence-Models

Transfer_Learning_Inception_v3

We test the accuracy of a single inception module, first developed by Google on MNIST. We then use an online repo of

stefannatu/Diffusion-Limited-Aggregation

2D Simulation modeling clustering of particles undergoing Brownian motion.

stefannatu/NLP-Translation-Models

Experimenting with different architectures for neural machine translation

stefannatu/amazon-a2i-sample-jupyter-notebooks

Sample Jupyter Notebooks for Amazon Augmented AI (A2I)

stefannatu/amazon-forecast-samples

Notebooks and examples on how to onboard and use various features of Amazon Forecast.

stefannatu/amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

stefannatu/amazon-sagemaker-studio-vpc-blog

stefannatu/Handling-large-imbalanced-data

Explore training large ML models at scale using Tensorflow APIs, sharding data, handling imbalanced data by training for precision/recall over accuracy

stefannatu/Semantic-Segmentation

Udacity Course -implement FCN for image segmentation

stefannatu/Sequence-to-Sequence-Models

stefannatu/Transfer_Learning_Inception_v3

We test the accuracy of a single inception module, first developed by Google on MNIST. We then use an online repo of

stefannatu/ModelMonitor

Model Monitor notebook for demo purposes

stefannatu/Pytorch-Chatbot

Chatbot implementation on Cornell movie dataset using Pytorch.

stefannatu/Sagemaker-examples

Sagemaker Tutorials

stefannatu/sagemaker-workshop

AWS Workshop for learning Amazon Sagemaker

stefannatu/Spark-ML-tutorial

PySpark tutorial on California Housing Dataset

stefannatu/tensorflow

An Open Source Machine Learning Framework for Everyone

stefannatu/Traffic-Dataset

We run a KNN algorithm and a convolutional network on the German Traffic Signs dataset

stefannatu/Wine_dataset