| # Install microk8s from the edge channel (Rancher requires Helm 2.15.1 or above) | |
| sudo snap install microk8s --classic | |
| # Enable useful plugins | |
| sudo microk8s.enable dns dashboard storage ingress helm | |
| # Allow running priviledged Pods (required by Rancher's `cattle-node-agent`) | |
| sudo sh -c 'echo "--allow-privileged=true" >> /var/snap/microk8s/current/args/kube-apiserver' | |
| sudo systemctl restart snap.microk8s.daemon-apiserver.service | |
| # Setup and install Tiller (part of Helm) |
See also: Free database hosting
| Service | Type | RAM | Storage | Limitations |
|---|---|---|---|---|
| AWS EC2 | IaaS | 1 GB | ||
| Azure App Service | PaaS | 1 GB | 1 GB | |
| Azure VM | IaaS | 1 GB | 2 GB (non-persistent) | |
| Google App Engine | PaaS | 128 MB | 1 GB | Standard Environment only Limited to Go, Java, Node.js, PHP, Python, Ruby; 1 GB/day outbound traffic |
| Google Compute Engine | IaaS | 0.6 GB | 30 GB | 1 GB/month outbound traffic (not including China or Australia). |
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| import matplotlib.pyplot as plt | |
| import keras.backend as K | |
| from keras.callbacks import Callback | |
| class LRFinder(Callback): | |
| ''' | |
| A simple callback for finding the optimal learning rate range for your model + dataset. | |
| """Keras 1.0 metrics. | |
| This file contains the precision, recall, and f1_score metrics which were | |
| removed from Keras by commit: a56b1a55182acf061b1eb2e2c86b48193a0e88f7 | |
| """ | |
| from keras import backend as K | |
| def precision(y_true, y_pred): | |
| """Precision metric. |
