01. Introduction To MLflow | Track Your Machine Learning Experiments | MLOps
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- Опубликовано: 18 окт 2024
- Welcome to our MLflow playlist, where we dive deep into the world of machine learning lifecycle management using the powerful open-source platform, MLflow. Whether you're a data scientist, machine learning engineer, or simply interested in the field of AI, this playlist is your guide to effectively managing and tracking your machine learning projects.
MLflow is a comprehensive toolset that helps you organize, track, and reproduce your machine learning experiments, enabling seamless collaboration and efficient deployment. In this playlist, we will explore various aspects of MLflow, from setting up the environment to leveraging its powerful features.
Join us as we take you through a step-by-step journey in harnessing the full potential of MLflow. We'll cover topics such as experiment tracking, version control, model packaging, and deployment. Learn how to streamline your machine learning workflow, improve experiment reproducibility, and simplify model deployment across different platforms.
Whether you're new to MLflow or already familiar with the basics, our playlist offers something for everyone. We'll provide in-depth tutorials, practical tips, and real-world examples to help you gain a comprehensive understanding of MLflow's capabilities.
Stay tuned for regular updates as we continue to explore advanced topics, share best practices, and showcase cutting-edge use cases in the field of machine learning lifecycle management. Subscribe to our channel and hit the notification bell to never miss an episode of our MLflow playlist.
Get ready to revolutionize your machine learning workflow with MLflow. Let's embark on this exciting journey together and unlock the true potential of your AI projects. Happy learning!
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It's really a fantastic explanation video for ML Flow.
Thank you
You are most welcome
Absolutely amazing, thank you so much for this video!
Great video for beginners, hands on showing made it interesting
thank god I found it after 2 days of starting ML flow
Very Nice
thank you so much Bappy
Thanks for Sharing your knowledge. it will be very helpful
Thanks :)
Nice job 👍
Thanks 👍
Hi , Thanks for the videos there are great . Needed help I used python3.8 & created env as yoiu suggested still getting error " mlflow.set_experiment(experiment_id="0")
AttributeError: partially initialized module 'mlflow' has no attribute 'set_experiment' (most likely due to a circular import)" - Any suggestions on this will be more then appreciated . I tried searching but didn't get an answer even gpt or google both
can you explain how I use the MLflow and visal studie together?
Very Cool Bro
Please, could you tell me which extension or setting do you use to predict code when typing?
tabnine
Hi
I got selected in an company where I have 2 options that i can choose devops engineer particularly using Mlflow role or ai/genai engineer to start my career
So could you please help me to choose which one has a better future..
what u chose bro???
Excellent Tutorial ✨
smoke and code challange, hit when Bappy says oké :)
such a great tutorial bro really appreciating for doing this
Thanks :)
very good tutorial
Is this going to be series??
Yes
bro please create dvc data versioning tutorials too.
Yes ,, its in pipeline
awesome bro
Thanks
awesome
thanks :)
🥳👏👏
Ok?
Ok.
OK
OK???? OK???? OK???? OK?????
every time you say ok you will give me 0.01$
hahaha
Bruh you talk too much unnecessarily for no reason? You literally start coding part at about 15 mins into the video which is stupid as its not even a super big topic that you need alot of theories beforehand, unnecessary yapping!
RUclips has skip option i think you forgot😜
@@dswithbappy nope, he didn’t add any in the timeline that will take you straight to the coding part
Woo, great playlist. clearly explained.
By the way , I can not see the forth tutorial , for some reason it shows "1 unavailable video is hidden"
would be upload soon