Pinned Repositories
cloud-dataproc
Samples for Cloud Dataproc
cloudml-samples
Cloud ML Engine is now a part of AI Platform
cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
CtCI-6th-Edition
Cracking the Coding Interview 6th Ed. Solutions
feast
Feature Store for Machine Learning
kubeflow
Machine Learning Toolkit for Kubernetes
kubeflow-pipelines
Machine Learning Pipelines for Kubeflow
mlflow
Open source platform for the machine learning lifecycle
tensorflow
An Open Source Machine Learning Framework for Everyone
tf-operator
Tools for ML/Tensorflow on Kubernetes.
mitakora's Repositories
mitakora/feast
Feature Store for Machine Learning
mitakora/kubeflow
Machine Learning Toolkit for Kubernetes
mitakora/kubeflow-pipelines
Machine Learning Pipelines for Kubeflow
mitakora/mlflow
Open source platform for the machine learning lifecycle
mitakora/tensorflow
An Open Source Machine Learning Framework for Everyone
mitakora/tf-operator
Tools for ML/Tensorflow on Kubernetes.
mitakora/cloud-dataproc
Samples for Cloud Dataproc
mitakora/cloudml-samples
Cloud ML Engine is now a part of AI Platform
mitakora/cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
mitakora/CtCI-6th-Edition
Cracking the Coding Interview 6th Ed. Solutions
mitakora/CtCI-6th-Edition-Python
Cracking the Coding Interview 6th Ed. Python Solutions
mitakora/Deep-Learning-with-TensorFlow-2-and-Keras
Deep Learning with TensorFlow 2 and Keras, published by Packt
mitakora/estimator
TensorFlow Estimator
mitakora/fpinscala
Code, exercises, answers, and hints to go along with the book "Functional Programming in Scala"
mitakora/kubeflow-examples
A repository to host extended examples and tutorials
mitakora/mlflow-workshop-part-1
Partly lecture and partly a hands-on tutorial and workshop, this is a three part series on how to get started with MLflow. In this three part series, we will cover MLflow Tracking, Projects, Models, and Model Registry.
mitakora/mlflow-workshop-part-2
Partly lecture and partly a hands-on tutorial and workshop, this is a three part series on how to get started with MLflow. In this four part series, we will cover MLflow Tracking, Projects, Models, and Model Registry.
mitakora/tensorflow-data-validation
Library for exploring and validating machine learning data
mitakora/tensorflow-hub
A library for transfer learning by reusing parts of TensorFlow models.
mitakora/tensorflow_cookbook
Code for Tensorflow Machine Learning Cookbook