Test_MLOps - Day 1 - Project Introduction & Setup | MLOPs Production Ready Machine Learning Project

https://www.youtube.com/watch?v=KF3MPzsnMdU&t=1088s

Anaconda: https://www.anaconda.com/ VS code: https://code.visualstudio.com/download Git: https://git-scm.com/ Flowchart: https://whimsical.com/ MLOPs Tool: https://www.evidentlyai.com/ MongoDB: https://account.mongodb.com/account/login Data link: https://www.kaggle.com/datasets/moro23/easyvisa-dataset

Basics of Machine Learning

1. Regression Tasks
2. Classification Tasks
3. Clustering Tasks

Setups:

Solotion Approach:

1. Machine Learning: ML Classificastion Algorithms
2. Deep Learning: Custom ANN (Artificial Nuro Network) with Sigmoid Activation Fundation

Solution Proposed: We will be using ML

1. Load the data from DB - Mongo DB
2. Perform EDA (Exploit Data Analysis) and fuature engineering to select the desirable features.
3. Fit the ML classification Algorithm and find out which one performs better.
4. Select the top few and tune hyperparameters. - Grid CV and Random CV - Optiona can also be used
5. Select the best model based on desired metrics.

Project Setup:

1. GitHub Repository - Project folder structure
2. Requirement instalations
3. Template cration

Mongo DB setup

Create a ne GitHub Project Get GitHub HTTP link, then open Git Bash Goto the folder you would like on Windows Explorer, Then open Git Bash window type "git clone "

in the Git Bash Terminal type "cd " Open this folder on VS by Right Click and select VS from the list.

How to commit changes done so far: Open VS with code: Type "code ." in Git Bash terminal

in the Git Bash Terminal type "git add ." git commit -m :" git push origin main