Pinned Repositories
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's Repositories
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