Here’s an overview of the new features and capabilities in the Azure Machine Learning Workbench application.
For more details, watch the session from Ignite 2017.
Fresh from the Ignite 2017 conference in Orlando, here is a great video on all the new features of Azure Machine Learning.
Most importantly, there’s great discussion of where ML Studio succeeded and what Azure Machine Learning will do better.
If you’ve heard the term “neural network” and was curious to exactly what it is, then watch this explainer video on the topic.
As many of you know, I have had a regular column in MSDN Magazine on UWP development for the past 18 months. However, today I am excited to announce that the column will now shift focus to Data Science, AI, and Machine Learning. This is a natural progression, given the direction of FranksWorld.com and the Data Driven podcast.
I’m even more excited to announce that the new column, called “Artificially Intelligent” is now available as of the October issue, which is online now.
Here’s a sample:
Over the last 10 years, the focus of many developer and IT organizations was the capture and storage of Big Data. During that time, the notion of what a “large” database size was grew in orders of magnitude from terabytes to petabytes. Now, in 2017, the rush is on to find insights, trends and predictions of the future based on the information buried in these large data stores. Combined with recent advancements in AI research, cloud-based analytics tools and ML algorithms, these large data stores can not only be mined, but monetized.
Here’s a great online tech talk about AI and Deep Learning at Amazon.
In this session:
- Learn about the breadth of AI services available on the AWS Cloud
- Gain insight into practical use cases for Amazon Lex, Amazon Polly, and Amazon Rekognition
- Understand why Amazon has selected MXNet as its deep learning framework of choice due its programmability, portability, and performance