dyerrington

Great Data Science Project Criteria:

• Problem statement that defines a measurable, and/or falsifiable outcome. “Frequency of [specific event] is influential over [some outcome]”. “Users who use [some feature in app] are differentiable from users who less frequently use [some feature in app]”. etc. If you can’t frame a data problem properly, none of has it has purpose. The biggest challenge in data science is making sense and defining the gray area of business problems. This also comes with experience.
• EDA EDA EDA. Define your scope. Report only what is necessary and relevant to your problem statement. If the model reports only 4-5 common variables as parameters (logistic regression for instance), focus on those when summarizing your work in terms of EDA.
• How much data is necessary to make this analysis work? Are you sampling? Is a t-test necessary to gain assurance or a rank order test?
• Explain which model makes the most sense to use. Are you trying to gain inference about a data problem?

zulhfreelancer

Just install Docker

$ curl -fsSL get.docker.com -o get-docker.sh && sh get-docker.sh

Install Docker and Rancher Server

$ curl -fsSL get.docker.com -o get-docker.sh && sh get-docker.sh && sudo docker run -d --restart=unless-stopped -p 8080:8080 rancher/server

wwwebman

version: '2'

services:
  db:
    container_name:  database
    image: mariadb  # Pull mysql image from Docker Hub
    ports:  # Set up ports exposed for other containers to connect to
      - "3306:3306"
    volumes:
      - ./dep/mysql:/docker-entrypoint-initdb.d

Dev-Dipesh

Redis is Database whereas RabbitMQ was designed as a message router or message-orientated-middleware (mom), so I'm sure if you look for benchmarks, you'll find that RabbitMQ will outperform Redis when it comes to message routing.

RabbitMQ is written in Erlang which was specifically designed by the telecom industry to route messages, you get clustering out of the box due to it being written in Erlang which means in a clustered environment, RabbitMQ will outperform Redis even further.

Furthermore, you get guaranteed delivery of messages due to the AMQP protocol, in other words, if the network drops while consuming the message, the consumer won't be able to say thanks for the message, so the consumer will drop the message and Rabbit will requeue the message, if you publish a message and the queue didn't say thanks to the publisher due to network problems or timeouts, Rabbit will drop the message and the publisher will keep on trying to publish the message. You can have publish retries with backoff policies, so