Highlights from the Connect(); conference

Connect();, the annual Microsoft developer conference, is wrapping up now in New York. The conference was the venue for a number of major announcements and talks. Here are some highlights related to data science, machine learning, and artificial intelligence: Lastly, I wanted to share this video presented at the conference from Stack Overflow. Keep an eye out for R community luminary David Robinson programming in R! You can find more from the Connect conference, including on-demand replays of the talks and keynotes, at the link below. Microsoft: Connect(); November 15-17, 2017
Original Post: Highlights from the Connect(); conference

How (& Why) Data Scientists and Data Engineers Should Share a Platform

[unable to retrieve full-text content]Sharing one platform has some obvious benefits for Data Science and Data Engineering teams, but technical, language and process challenges often make this a challenge. Learn how one company implemented single cloud platform for R, Python and other workloads – and some of the unexpected benefits they discovered along the way.
Original Post: How (& Why) Data Scientists and Data Engineers Should Share a Platform

Best Data Science, Machine Learning Courses from Udemy, only $10 until Nov 28- Black Friday/Cybermonday sale

[unable to retrieve full-text content]Black Friday/Cybermonday sale on best courses from Udemy, including Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop – only $10 until Nov 28, 2017.
Original Post: Best Data Science, Machine Learning Courses from Udemy, only until Nov 28- Black Friday/Cybermonday sale

Top 10 Videos on Deep Learning in Python

[unable to retrieve full-text content]Playlists, individual tutorials (not part of a playlist) and online courses on Deep Learning (DL) in Python using the Keras, Theano, TensorFlow and PyTorch libraries. Assumes no prior knowledge. These videos cover all skill levels and time constraints!
Original Post: Top 10 Videos on Deep Learning in Python

PySpark SQL Cheat Sheet: Big Data in Python

[unable to retrieve full-text content]PySpark is a Spark Python API that exposes the Spark programming model to Python – With it, you can speed up analytic applications. With Spark, you can get started with big data processing, as it has built-in modules for streaming, SQL, machine learning and graph processing.
Original Post: PySpark SQL Cheat Sheet: Big Data in Python

Developing AI applications on Azure: learning plans at three levels

If you’re looking to expand your skills as an AI developer, or just getting started, these learning plans for AI Developers on Azure provide a wealth of information to get you up to speed. The beginner, intermediate and advanced tracks all provide step-by-step guides to setting up the tools and data in Azure, along with worked examples in iPython Notebooks. The Beginner AI Developer Learning Plan provides an introduction to artificial intelligence and cognitive systems. It begins with an overview of Cognitive Services, and then works through several examples of using those APIs in applications: handwriting comprehension, speech comprehension, and face detection. The Intermediate AI Developer Learning Plan walks through the process of creating an AI application that understands voice input. It begins with an overview of LUIS, the Language Understanding Intelligent Service, and walks through the process of defining intents, entities,…
Original Post: Developing AI applications on Azure: learning plans at three levels

TensorFlow: What Parameters to Optimize?

[unable to retrieve full-text content]Learning TensorFlow Core API, which is the lowest level API in TensorFlow, is a very good step for starting learning TensorFlow because it let you understand the kernel of the library. Here is a very simple example of TensorFlow Core API in which we create and train a linear regression model.
Original Post: TensorFlow: What Parameters to Optimize?

Top KDnuggets tweets, Nov 01-07: Airbnb develops an #AI which converts design into source code

[unable to retrieve full-text content]Also: One LEGO at a time: Explaining the #Math of How #NeuralNetworks Learn; 6 Books Every #DataScientist Should Keep Nearby; Direct from Sebastian Raschka #Python #MachineLearning book, new edition.
Original Post: Top KDnuggets tweets, Nov 01-07: Airbnb develops an #AI which converts design into source code