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README.md

1. Introduction

Instructor: Alexey Grigorev

1.1 Introduction

1.2 Environment preparation

Note: You don't have to rent an instance in the cloud. You can follow the same instructions for setting up your local environment.

Code:

Recommended development environment: Linux

Step 1: Download and install the Anaconda distribution of Python

wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh

Step 2: Update existing packages

sudo apt update

Step 3: Install Docker

sudo apt install docker.io

Step 4: Install Docker Compose

4.1 Install docker-compose in a separate directory

mkdir soft
cd soft

4.2 To get the latest release of Docker Compose, go to https://github.com/docker/compose and download the release for your OS.

wget https://github.com/docker/compose/releases/download/v2.5.0/docker-compose-linux-x86_64 -O docker-compose

4.3 Make it executable

chmod +x docker-compose

4.4 Add to path

nano .bashrc

In .bashrc, add:

export PATH="${HOME}/soft:${PATH}"

Run

source .bashrc

Run Docker without sudo

sudo groupadd docker
sudo usermod -aG docker $USER

Step 5: Run Docker

docker run hello-world

1.3 (Optional) Training a ride duration prediction model

Note: The NYC taxi data is now in parquet format, not CSV. Here's a video that explains how to read parquet data.

Links:

1.4 Course overview

1.5 MLOps maturity model

Links:

1.6 Homework

More information here: homework.md

Notes

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