This is GoldMine for MLFlow deployement . Thanks for sharing such Gold Mine content.

Thank you so much, Dada! Your works are really helpful! Keep working and guide us; distribute your knowledge, experience and good things!

any technique or library helps to detect model drift ....? thanks in advance ☺️

nice insight !

Thank sir, after hours of trying I finally can install it

Do you see, near feature challenges in data quality ethical concerns and scalability?

Very good 👍

Very insighful!

Your work is really impressive. I have been following your videos and gaining a lot of knowledge. excellent work...keep it up!!!

Sir, can we used feast for image data? How can implement it? actually saw your video on feast on machine learning model. I am trying implement for image data for image classification, but I have got error. sir can you make video on it. thank you

i am hosting mlflow on VM and using set tracking URI to log parameters , metrics , artifacts , my model is not supported by mlflow so to log i am using pyfunc module of mlflow to log the model. i have written custom class like ........ class Model_Wrapper(mlflow.pyfunc.PythonModel): def __init__(self,): self.model = None def load_context(self,context): self.model=mlflow.pyfunc.load_model(context.artifacts["Original_Model"]) def predict(self, context, model_input): ss=self.model.sample(model_input.get("records")[0]) return ss.to_json() passing {"inputs":{"records":[20]}} for invocations url in postman.. but, getting error as....... Encountered an unexpected error while evaluating the model. Verify that the serialized input Dataframe is compatible with the model for inference. I am using SDV ctgan model can you help anything on this...

This is a wonderful explanation of the MLflow implementation....thanks for the efforts and making the learner's understanding very simple yet effective...good work...

Thanks a lo sir

Great video. Strait to the point. l love it.

🎉 waited for this video

Reproducible data and ML Pipeline using DVC: kzfaq.info/get/bejne/ZsyKpryFrNWsYHU.htmlsi=BBZzBuGQ8w0zgQF4

Data Version Control Live Demo: kzfaq.info/get/bejne/o9yfgr2lusDdfnk.htmlsi=vBnwnNkUILgKw586 Setup gsutil to access gs cloud buckets: kzfaq.info/get/bejne/oaeXZ7eAlZnXnHU.htmlsi=neGC5hrjEmt1-_Ob

very well explained. Thanks Ashutosh.

can we get answer for anyu question..? or the data which was already provided..?

great sir

when i called entity_df = pd.DataFrame({ "movie_id": [1, 2, 3], "event_timestamp": pd.to_datetime(["2024-07-29", "2024-07-29", "2024-07-29"]) }) # Получение исторических данных historical_features = fs.get_historical_features( entity_df=entity_df, features=[ "movies_1980_2020:title", "movies_1980_2020:director", "movies_1980_2020:genre", "movies_1980_2020:release_date", "movies_1980_2020:duration", "movies_1980_2020:rating" ] ).to_df() I have some problem. -> 6252 raise KeyError(f"{not_found} not in index") KeyError: "['title', 'director', 'genre', 'release_date', 'duration', 'rating'] not in index"

Thanks for the video. can you please make a video on model governance as well?

Good job

Awesome Tutorial...

Awesome Tutorial...

Hello Ashutosh , Thank for explaining everything in details its really Helpful , I have a question , - Can we acheive CI/CD in Machine learning with MLflow ? - Why do we use kubeflow is it different from MLflow ? - Which solution MLflow or Kubeflow is widly in Industry Practise ?

how can we run all the code in the background as in run/set it on the server so everything still runs when we leave the environment?

Hi, Getting the below error PS D:\Software\airflow-docker> docker compose up airflow-init time="2024-07-23T15:42:52+05:30" level=warning msg="The \"AIRFLOW_UID\" variable is not set. Defaulting to a blank string." time="2024-07-23T15:42:52+05:30" level=warning msg="The \"AIRFLOW_UID\" variable is not set. Defaulting to a blank string." error during connect: Get "%2F%2F.%2Fpipe%2FdockerDesktopLinuxEngine/v1.46/containers/json?all=1&filters=%7B%22label%22%3A%7B%22com.docker.compose.config-hash%22%3Atrue%2C%22com.docker.compose.project%3Dairflow-docker%22%3Atrue%7D%7D": open //./pipe/dockerDesktopLinuxEngine: The system cannot find the file specified.

Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'SSLEOFError(8, 'EOF occurred in violation of protocol (_ssl.c:2427)')': /pkgs/main/notices.json

Hi Ashutosh, Great Video. So you are using Paid LLM here? If yes, then how can we do this with open-source or free llm's?

Great tutorial

Thanks

Great ashtouch!!. More contents on complex pipelines pls, with third party connectors too.

Great content ashtouch.. we need consistent content on airflow pls. Perhaps a paid course is in the works?

after kubectl apply -f tensorflow.yaml my pod running state shows 1/2 instead of 2/2. How to resolve that?

Where is the video you mebtuobed in 12:03 ? how to create (and run?) a pipeline

bro for me those containers are not created...i followed all the steps.if i search for loaclhost:8088 it says congratulations you have created your first container

Can you start AIops series

Binary file of Model will be of what extension?

Not working internally you used a openAi key iguess

Good work im gonna try now. Please use the milvus for the vectors

Very good in

the best mlflow i first seen

Great insight Ashutosh,thanks a lot

Thanks you ashutosh you are awesome teacher thanks for very clear explanation of each thing Kindly please clear my below doubts Do we use gunicorn server in production?if no then why we dont use and which one we use another question is if i am working as Mlops engineer then do i need to create Docker file and requirmemnt.txt myself or we will get it from developer how it works ?

Thank you sir

The video is soo dam good u r a gem

Can we use text to speech and speech to text api's for the outputs?

Nice

Thank you so much for this video! 12:27 onwards helped me solve an issue I was facing for a long time with python packages not found.