Devon Crawford explains the fundamentals of coding C/C++ in just over eight minutes.
While I wouldn’t say it would replace a computer science degree, it’s a great jump into C, a language that inspires fear and awe.
While in Vegas, I caught up with my former DataLeader pal, Kim Schmidt to talk about her new book, advanced analytics, and why Microsoft, Google, and Amazon are the Ford, GM, and Chrysler of the 21st century.
Press the play button below to listen here or visit the show page at DataDriven.tv
As I drove back from Reston today in bumper to bumper Beltway traffic, I longed for the day when I can get a self-driving car. To be fair, I did make productive use of my time by recording a live stream for Data Driven.
Transport Systems Catapult in the UK has been looking at automated pod vehicles. Senior Technologist Rebecca Advani explains the LUTZ Pod system.
YouTuber Jabrils shares his history of how he got into machine learning, what inspired him, and about his first machine learning game.
Plus, some cool dance moves during his re-enactment of making his first neural network.
CSS, while powerful, is the bane of many web developer’s existence. In this Five Things video, Burke sits down with CSS ninja Aimee Knight to bring you Five useful tips for working with CSS.
Just when you thought Azure Databricks couldn’t get any better, watch this video where Yatharth Gupta, Principal Program Manager for Azure Databricks, talks about the newly introduced integration with R Studio.
For data scientists looking at scaling out R-based computing to big data, Azure Databricks provides the best way scale out their R models with Spark, that is easy to setup and integrates with the most popular R tools and frameworks. Data scientists can use Azure Databricks and R Studio to easily create analytics models, quickly access and prepare high quality data sets, and automatically run R workloads at unprecedented scale.
In this video, Katherine Kampf, PM on Azure Big Data team, talks about the newly introduced ML Services in Azure HDInsight.
ML Services bridges these Microsoft innovations and contributions coming from the open-source community (R, Python, and AI toolkits) all on top of a single enterprise-grade platform. Any R or Python open-source machine learning package can work side by side with any proprietary innovation from Microsoft.
ML Services includes highly scalable, distributed set of algorithms such as RevoscaleR, revoscalepy, and microsoftML that can work on data sizes larger than the size of physical memory, and run on a wide variety of platforms in a distributed manner.
Siraj Raval has some advice for people looking to break into the Machine Learning/AI field for the first time with some resume tips.