ai
6 TopicsPush for hyperrealistic AI Video Generator
I fervently believe that Microsoft must pioneer the development of AI-generated videos. OpenAI has already set the stage with Sora, and if Microsoft doesn't act now, it risks falling behind in the fiercely competitive AI market. This isn't just about keeping paceāit's about leading the charge. Furthermore, the rollout of AI-generated videos must be nothing short of exceptional. These videos need to boast impeccable quality and clearly convey the intended content. Mediocrity has no place in this vision. And let's not forget about preparing Clipchamp for the 2030s. It's imperative to equip it with cutting-edge capabilities that will redefine video creation and editing for the future. Together, these initiatives will not only keep Microsoft at the forefront but will also revolutionize the AI and video landscape.41Views0likes0CommentsAI Fluency GitHub Course
Hi there, not sure if I'm posting in the correct place for my query. I found a course on AI Fluency on Microsoft's GitHub repository. Is this course linked anywhere on the Microsoft website as a referral, eg from learn.microsoft.com, or something along those lines?84Views0likes0CommentsJumping from Google's Teachable Machine to Azure. Help
I've been using Google's Teachable Machine for experiments for months, using two classes of images to train for recognition. I now need to switch the data source to tabular data (TM doesn't support this), and feel as though I've walked into Costco, Home Depot and Walgreens combined, with Azure. I've reviewed libraries of demos at studio.azureml.net and signed up for something else related to Azure, but, beyond uploading data, I have yet to find a way to replicate the workflow and simplicity of setup Teachable Machine offered. Any guidance is appreciated as (now knowing 9 computer programming languages) I'm not keen on learning yet another "ecosystem" over the course of X months.1.3KViews0likes0CommentsCan we use Azure Machine Learning on a Azure Analysis Services?
Hello, it's my first post ever since i was hired as Data Scientist after graduating this month. Of course, i have no experience in any cloud microsoft techonologies (yet) and ask for forgiveness in advance if I mix concepts incorrectly. Also, i tried to search similar answers in the forum but sadly found nothing. In our business, we deployed an Azure Analysis Services with our data models ( i think it's called datalake). These models are used most of them for Reporting in Power BI. Right now, we would like to explore more deep types of analysis using machine learning techniques in Azure Machine Learning. The basic problem is how do i acces to the information in the tabular models in Azure Analysis Services from Azure Machine learning? Is this new platform (Azure ML) able to do that easily, without any trick? For example, we tried to make some querys (to Azure Analysis Services) from our locals, using python and pyodbc library. This never worked and there's no information (at least i've found) in the internet. The reason to use python to make querys it's for practical reasons. You make the query, and you call still work on the same notebook without downloading anything externaly, then throw X machine learning algorithm to do Classification, Regression... in the data selected in the query to make a Exploratory Data Analysis. So our idea, would be to replace this locals machines for something in the cloud which i hope have a direct implementation to work with that and also better hardware. Am i wrong, right...? Do you have any suggestion of how we should do things? Please, correct me! Thank you for your answer!2.2KViews1like1Commentcommon pitfall of using data bricks with pandas and not spark
Hi Team, I just want to understand what could be the common pitfall of using Pandas on Databricks instead of Spark. There are certain factors on which we have decided to go with Databricks instead of Azure AI platform (jupyter notebook). Experiment tracking using ML-ops Hyperparameter tuning with Spark trails which helps with parallelization I just wanted to understand that what could possibly go wrong if we train model on Databricks by just using pandas & sklearn . Deployment: we will deploy final model offline, will different env will cause an issue ? Cost: is AI platform supports points mentioned above, experiment tracking & parallel hyperparameter tuning Ease of use other advantage offered by AI platform (ex: automatic hyperparameter tuning) I am new to Azure service, It will be really helpful if you can share detail answer of above points with your preference. (what you would have chosen and why?) Thanks in Advance.903Views0likes0Comments