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

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  • Опубліковано 5 вер 2024
  • 🚀MLOps Production Ready Machine Learning Project 🚀
    🚀 Welcome to our comprehensive guide on creating a production-ready machine learning project using MLOps! In this video, we will walk you through every step needed to successfully deploy and manage your machine learning models in a production environment.
    📌Code: github.com/ent...
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КОМЕНТАРІ • 24

  • @utkar1
    @utkar1 2 місяці тому +2

    07:13 - Prerequisites
    13:56 - Setup
    19:57 - Project discussion
    24:42 - Problem statement
    27:22 - Features
    28:14 - Solution scope
    29:04 - Solution approach
    31:56 - Solution proposed
    35:19 - Project setup
    36:08 - MongoDB setup
    37:24 - Github repository setup
    41:50 - Folder structure setup
    01:20:38 - requirements.txt

  • @aliaamir9778
    @aliaamir9778 2 місяці тому

    dear Bappy , i also saw that you are part of ineuron team along with krish naik sahab, just wanted to request to please take one multivariate timeseries regression problem and solve it as a end to end MLOPS deep learning project, because i am only able to explore all of your and krish naik projects based on computer vision and machine learning, but anyhow i really appreciate your efforts , this is rare content on youtube. Love from Pakistan,

  • @utkar1
    @utkar1 2 місяці тому

    Thanks Bappy, appreciate your efforts! Looking forward to the next one!

  • @binnypero6431
    @binnypero6431 26 днів тому

    54:25 - Importance of project organization and folder structure.
    01:00:47 - Creating a project folder structure automatically using Python scripts.
    01:01:01 - Creation of essential components like configuration and constants.
    01:03:16 - Differences in path handling between operating systems.
    01:08:04 - Automation through scripts to reduce manual effort.
    01:10:51 - Introduction of a website for creating flowcharts and the tool Evidently.
    01:11:14 - Creating diverse flowcharts for better understanding data workflows.
    01:13:22 - Evidently for monitoring AI applications and detecting data discrepancies.
    01:14:39 - Focused approach in using ML tools for project simplicity.
    01:20:55 - Guide on using Git commands and creating a Python environment.
    01:20:56 - Demonstration of basic Git commands for version control.
    01:21:11 - Discussion on creating a project environment with conda.
    01:22:40 - Installation of necessary packages for the project.
    01:30:59 - Importance of understanding Python's stable versions.
    01:31:13 - Release cycle of Python versions and their support.
    01:34:39 - Incorporating CI/CD tools like GitHub Actions and Jenkins.
    01:38:40 - Importance of coding in environments like Jupyter notebooks.
    01:03 - Mastering modular coding in Python for machine learning projects.
    01:52 - Importance of installing packages like XGBoost and CatBoost.
    06:02 - Plans to integrate Jenkins into future projects.
    07:43 - Significance of setting up a proper development environment.
    01:55:42 - Exploration in learning to broaden knowledge.
    01:58:44 - Importance of GitHub for sharing code and collaboration.
    01:58:51 - Practical application of learned skills through hands-on projects.
    01:59:09 - Upcoming sessions on MongoDB setup and data management.

  • @mahetsiedahi6530
    @mahetsiedahi6530 Місяць тому

    thnks Bappy for your contribution, you have a great way of explaining, it motivates me to keep learning and overcome certain fears professionally. I hope you continue sharing knowledge and thank you again for the inspiration...Greetings from Mexico!

  • @akashjoy.V1
    @akashjoy.V1 Місяць тому

    Thank you brother. Excellent content. Can you please drop a schedule to something before you go live so that we can be ready ?

  • @kashifsadiq4145
    @kashifsadiq4145 2 місяці тому +1

    Sir plzzz more focus on ops or deployment part. Kubeflow. Air flow kubernetes seldon monitoring Kserve

  • @QuanVan-s8s
    @QuanVan-s8s 2 місяці тому

    Thank you so much!

  • @MDAsadullahShibli
    @MDAsadullahShibli 2 місяці тому

    well explained !!

  • @sumankumar01
    @sumankumar01 Місяць тому +1

    Stuck at environment creation. Can someone help pls

  • @singhamrinder50
    @singhamrinder50 2 місяці тому

    Awesome video

  • @zuhairansari1178
    @zuhairansari1178 2 місяці тому

    Great Video Brother ❤

  • @jatinsareen7771
    @jatinsareen7771 2 місяці тому +1

    Great session!!
    But why did you leave ineuron and why others are also leaving it?? will ineuron get closed??

  • @user-uc9wp8mx3j
    @user-uc9wp8mx3j Місяць тому

    THanks for the session. Its very informative. I just have one question.
    Is this the way how companies setup the things and have these folders for the codebase while working on real world problems

  • @soumyajitsahu3972
    @soumyajitsahu3972 Місяць тому

    can you please start genai project parallely . Thank you for your so much valuable videos. Your Videoes are so valuable somuch details.

  • @sumankumar01
    @sumankumar01 Місяць тому

    @dswithbappy You have not instructed to activate Conda environment inside git bash. none of the python commands would run. Please add that part in the video.

  • @rezamahmoudi163
    @rezamahmoudi163 Місяць тому

    thanks , please share powerpoint share ?

  • @alhasanmohammedbinquraish960
    @alhasanmohammedbinquraish960 2 місяці тому +1

    Hindi mlops video sir 🙏🙏🙏