Even if we are still a couple of days away of the official International Women Day, let me share my contributions and plan for the future.
My main 2 cents to the International Women Days is kind of selfish, however I strongly believe that support and encourage new generations to get close to STEM topics is a great way to support them.
That’s why, if you can, I strongly encourage to bring your kids (and/or your kid’s friends) to tech events. Share moments with them, introduce them to the speakers, attendees, helpers, etc on the event. They will learn new stuff; they will share some amazing ideas, and this is an amazing path for them to learn and know STEM!
It’s also important for us to acknowledge that men and women have different workplace experiences, so that’s why I hope that next generations won’t see a difference there.
And finally, please, let’s keep talking about this. I’m not an expert in this area, and the best I can do is to connect the dots and support some very specific scenarios. I’ll keep doing this !
And yes, Martina is also helping me now with my Drone and AI pet projects. You can see how much fun our pet Goku is having with the drone
Thanks Channel 9 and On.Net !
Note: And it seems that the other half of the family is not happy to be excluded of this post.
Tailwind Traders has a lot of legacy data that they’d like their developers to leverage in their apps – from various sources, both structured and unstructured, and including images, forms, and several others. In this session, learn how the team used Azure Cognitive Search to make sense of this data in a short amount of time and with amazing success. We discuss tons of AI concepts, like the ingest-enrich-explore pattern, search skillsets, cognitive skills, natural language processing, computer vision, and beyond.VIEW MORE
Using pre-built AI to solve business challenges
As a data-driven company, Tailwind Traders understands the importance of using artificial intelligence to improve business processes and delight customers. Before investing in an AI team, their existing developers were able to demonstrate some quick wins using pre-built AI technologies. In this session, we show how you can use Azure Cognitive Services to extract insights from retail data and go into the neural networks behind computer vision. Learn how it works and how to augment the pre-built AI with your own images for custom image recognition applications.VIEW MORE
Start building machine learning models faster than you think
Tailwind Traders uses custom machine learning models to fix their inventory issues – without changing their software development life cycle! How? Azure Machine Learning Visual Interface. In this session, learn the data science process that Tailwind Traders’ uses and get an introduction to Azure Machine Learning Visual Interface. See how to find, import, and prepare data, select a machine learning algorithm, train and test the model, and deploy a complete model to an API. Get the tips, best practices, and resources you and your development team need to continue your machine learning journey, build your first model, and more.VIEW MORE
Taking models to the next level with Azure Machine Learning best practices
Tailwind Traders’ data science team uses natural language processing (NLP), and recently discovered how to fine tune and build a baseline models with Automated ML. In this session, learn what Automated ML is and why it’s so powerful, then dive into how to improve upon baseline models using examples from the NLP best practices repository. We highlight Azure Machine Learning key features and how you can apply them to your organization, including: low priority compute instances, distributed training with auto scale, hyperparameter optimization, collaboration, logging, and deployment.VIEW MORE
Machine learning operations: Applying DevOps to data science
Many companies have adopted DevOps practices to improve their software delivery, but these same techniques are rarely applied to machine learning projects. Collaboration between developers and data scientists can be limited and deploying models to production in a consistent, trustworthy way is often a pipe dream. In this session, learn how Tailwind Traders applied DevOps practices to their machine learning projects using Azure DevOps and Azure Machine Learning Service. We show automated training, scoring, and storage of versioned models, wrap the models in Docker containers, and deploy them to Azure Container Instances or Azure Kubernetes Service. We even collect continuous feedback on model behavior so we know when to retrain.VIEW MORE
Download all the slides and videos
And, finally if you want all these sessions material, just
Access “Get the bulk session resource download script” at the bottom of the page in one of the sessions.
Open a PowerShell window to the directory in which the script is located.
you are curious, you can also see the “Get the bulk session resource download
script” at the bottom of the page. This action will download a zip file with 2
file is a script to download all the videos from Microsoft Ignite! That’s
amazing. Of course, there are a couple of parameters to use, so you can only
download what you need.
To run the
script, open a PowerShell window to the directory in which the script is
To download everything run the following .\Download-Resources.ps1 To download everything into a given directory run the following .\Download-Resources.ps1 "C:\Microsoft Ignite" To download a set of sessions, supply the session code like this: .\Download-Resources.ps1 -directory . -sessionCodes "KEY,TK01,TK02,BRK3016"
If you want more details and a better process, you can read my friend Guy post using a similar script to download Microsoft Ignite 2019 materials (see references)
When I was in Ohio @CodeMash, I was lucky enough to meet Jennifer Marsman, Principal Engineer & speaker on the AI for Earth team at Microsoft (@jennifermarsman). She hosted an amazing session where she shared details about some projects on AI for Earth.
AI for Earth puts Microsoft cloud and AI tools in the hands of those working to solve global environmental challenges
The work that the AI for Earth teams are doing are amazing, and I was really impressed by the “Mexican whale story”. The team uses image analysis to identify individual animals in regular persons photos or videos, and using meta data like date and location of a photo or a video, they can generate paths of animal migration. And yes, the photos came from public social media spaces like Facebook, Instagram or YouTube.
So, I got this information as a draft for a while, and now I get some more details and it makes sense to share it. The project name is Wild Me:
Wild Me is using computer vision and deep learning algorithms to power Wildbook, a platform that can identify individual animals within a species. They also augment their data with an intelligent agent that can mine social media.
And as usual, a video is the best way to explain this:
Besides Wild Me, there are other amazing projects like SilviaTerra or FarmBeats. You can find the complete list of projects and challenges here (link).