| { | |
| "created_at": "Wed Jul 03 18:51:49 +0000 2019", | |
| "id": 1146491754239033300, | |
| "id_str": "1146491754239033344", | |
| "text": "RT @manishrjain: Contains my favorite StreamWriter API -- At 1.6 Gbps, it's the fastest way to bootstrap a new badger instance. https://t.c…", | |
| "truncated": false, | |
| "entities": { | |
| "hashtags": [], | |
| "symbols": [], | |
| "user_mentions": [ |
| version: "3.5" | |
| services: | |
| alpha1: | |
| image: dgraph/dgraph:v1.0.13 | |
| container_name: alpha1 | |
| working_dir: /working/alpha1 | |
| labels: | |
| cluster: flock-cluster | |
| ports: | |
| - 8180:8180 |
| version: "3.2" | |
| services: | |
| zero: | |
| image: dgraph/dgraph:latest | |
| volumes: | |
| - type: volume | |
| source: dgraph | |
| target: /dgraph | |
| volume: | |
| nocopy: true |
| import tensorflow as tf | |
| import numpy as np | |
| # Allow data to be supplied later during execution. | |
| A = tf.placeholder(tf.int32, shape=(2, 2)) | |
| x = tf.placeholder(tf.int32, shape=(2, 1) ) | |
| # Define the matrix multiplication operation. |
Step-1. Download the binary of prometheus
[prometheus-binary] (curl -LO https://github.com/prometheus/prometheus/releases/download/v2.8.0/prometheus-2.8.0.linux-amd64.tar.gz) download and unpack the current stable version of Prometheus into your home directory.
Step-2. Extract the tar file using below command
tar xvf prometheus-2.8.0.linux-amd64.tar.gz
| <?xml version="1.0" encoding="UTF-8"?> | |
| <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> | |
| <configuration> | |
| <property> | |
| <name>fs.s3a.endpoint</name> | |
| <description>AWS S3 endpoint to connect to. An up-to-date list is | |
| provided in the AWS Documentation: regions and endpoints. Without this | |
| property, the standard region (s3.amazonaws.com) is assumed. | |
| </description> |
We are Kredaro, an early stage startup focussed on solution offering on these following broad areas and their respective sub-categories, our core competency revolves around tailoring solutions for challenges @Scale.
| compute_rmse = """ | |
| #standardSQL | |
| SELECT | |
| IF(MOD(ABS(FARM_FINGERPRINT(date)), 10) < 8, 'train', 'eval') AS dataset, | |
| SQRT(AVG((arrival_delay - ALPHA * departure_delay)*(arrival_delay - ALPHA * departure_delay))) AS rmse, | |
| COUNT(arrival_delay) AS num_flights | |
| FROM | |
| `bigquery-samples.airline_ontime_data.flights` | |
| WHERE | |
| departure_airport = 'DEN' |
| piVersion: networking.istio.io/v1alpha3 | |
| kind: Gateway | |
| metadata: | |
| name: up-gateway | |
| namespace: istio-system | |
| spec: | |
| selector: | |
| istio: ingressgateway # use Istio default gateway implementation | |
| servers: | |
| - port: |
| import tensorflow as tf | |
| hidden_layer_weights = [ | |
| [0.1, 0.2, 0.4], | |
| [0.4, 0.6, 0.6], | |
| [0.5, 0.9, 0.1], | |
| [0.8, 0.2, 0.8]] | |
| out_weights = [ | |
| [0.1, 0.6], |