All Projects → tensorflow → Tpu

tensorflow / Tpu

Licence: apache-2.0
Reference models and tools for Cloud TPUs.

Programming Languages

Jupyter Notebook
11667 projects
python
139335 projects - #7 most used programming language
c
50402 projects - #5 most used programming language
go
31211 projects - #10 most used programming language
shell
77523 projects
Dockerfile
14818 projects

Projects that are alternatives of or similar to Tpu

Tcav
Code for the TCAV ML interpretability project
Stars: ✭ 442 (-90.35%)
Mutual labels:  jupyter-notebook
3dmol.js
WebGL accelerated JavaScript molecular graphics library
Stars: ✭ 443 (-90.33%)
Mutual labels:  jupyter-notebook
Pytorch advanced
書籍「つくりながら学ぶ! PyTorchによる発展ディープラーニング」の実装コードを配置したリポジトリです
Stars: ✭ 448 (-90.22%)
Mutual labels:  jupyter-notebook
Python Ml Course
Curso de Introducción a Machine Learning con Python
Stars: ✭ 442 (-90.35%)
Mutual labels:  jupyter-notebook
Swiftai
Swift for TensorFlow's high-level API, modeled after fastai
Stars: ✭ 445 (-90.28%)
Mutual labels:  jupyter-notebook
Jupyter tensorboard
Start Tensorboard in Jupyter Notebook
Stars: ✭ 446 (-90.26%)
Mutual labels:  jupyter-notebook
Practical Deep Learning Book
Official code repo for the O'Reilly Book - Practical Deep Learning for Cloud, Mobile & Edge
Stars: ✭ 441 (-90.37%)
Mutual labels:  jupyter-notebook
Ipython Soccer Predictions
Sample iPython notebook with soccer predictions
Stars: ✭ 447 (-90.24%)
Mutual labels:  jupyter-notebook
Orion
A machine learning library for detecting anomalies in signals.
Stars: ✭ 445 (-90.28%)
Mutual labels:  jupyter-notebook
Pytorch Fastcampus
PyTorch로 시작하는 딥러닝 입문 CAMP (2017.7~2017.12) 강의자료
Stars: ✭ 447 (-90.24%)
Mutual labels:  jupyter-notebook
Modsimpy
Text and supporting code for Modeling and Simulation in Python
Stars: ✭ 443 (-90.33%)
Mutual labels:  jupyter-notebook
Deeplearning Ahem Detector
Stars: ✭ 444 (-90.31%)
Mutual labels:  jupyter-notebook
Dynslam
Master's Thesis on Simultaneous Localization and Mapping in dynamic environments. Separately reconstructs both the static environment and the dynamic objects from it, such as cars.
Stars: ✭ 446 (-90.26%)
Mutual labels:  jupyter-notebook
Publaynet
Stars: ✭ 442 (-90.35%)
Mutual labels:  jupyter-notebook
D2 Net
D2-Net: A Trainable CNN for Joint Description and Detection of Local Features
Stars: ✭ 448 (-90.22%)
Mutual labels:  jupyter-notebook
Reinforcement learning tutorial with demo
Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..
Stars: ✭ 442 (-90.35%)
Mutual labels:  jupyter-notebook
Face Image Motion Model
Face Image Motion Model (Photo-2-Video) based on "first-order-model" repository.
Stars: ✭ 446 (-90.26%)
Mutual labels:  jupyter-notebook
Course V4
Please use fastbook's /clean folder instead of this
Stars: ✭ 449 (-90.2%)
Mutual labels:  jupyter-notebook
Course Resources Ml With Experts Budgets
Further student resources for DrivenData's 'Machine Learning with the Experts: School Budgets' DataCamp course.
Stars: ✭ 447 (-90.24%)
Mutual labels:  jupyter-notebook
Rl Portfolio Management
Attempting to replicate "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" https://arxiv.org/abs/1706.10059 (and an openai gym environment)
Stars: ✭ 447 (-90.24%)
Mutual labels:  jupyter-notebook

Cloud TPUs

This repository is a collection of reference models and tools used with Cloud TPUs.

The fastest way to get started training a model on a Cloud TPU is by following the tutorial. Click the button below to launch the tutorial using Google Cloud Shell.

Open in Cloud Shell

Note: This repository is a public mirror, pull requests will not be accepted. Please file an issue if you have a feature or bug request.

Running Models

To run models in the models subdirectory, you may need to add the top-level /models folder to the Python path with the command:

export PYTHONPATH="$PYTHONPATH:/path/to/models"
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].