[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
[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
[unable to retrieve full-text content]TDWI provides the in-depth, vendor-neutral training in business analytics, data science, and data management, including a certificate track. Save 30% thru Dec 15, 2017 with code KD30.
Original Post: We Speak Data at TDWI Las Vegas, Feb 11-16. Save w. code KD30 thru Dec 15
[unable to retrieve full-text content]Seeking a Machine Learning-Industrial Methods Engineer to collaborate with mechanical and quality engineers to apply machine learning to industrial problems and situations and identify new opportunities in to apply machine learning tools.
Original Post: Apple: Machine Learning-Industrial Methods Engineer
[unable to retrieve full-text content]Second part of this incredible overview of Generative Adversarial Networks, explaining the contributions of Deep Convolutional-GAN (DCGAN) paper.
Original Post: Generative Adversarial Networks — Part II
[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
[unable to retrieve full-text content]If you develop methods for data analysis, you might only be conducting gentle tests of your method on idealized data. This leads to “fragile research,” which breaks when released into the wild. Here, I share 3 ways to make your methods robust.
Original Post: Stop Doing Fragile Research
[unable to retrieve full-text content]Seeking a Director, Data Science & Analytics, to be responsible for oversight and strategic direction of advanced analytics, including predictive modeling, that drive business performance consistent with company goals and objectives.
Original Post: American Family Insurance: Director, Data Science & Analytics
[unable to retrieve full-text content]Two years. Two years is the maximum amount of time you should spend focused on your learning, education and training. That’s exactly why this guide is focused on honing the most beneficial skills in two years.
Original Post: 8 Ways to Improve Your Data Science Skills in 2 Years
[unable to retrieve full-text content]Jen Underwood will review how to organize data in a machine learning-friendly format that accurately reflects the business process and outcomes.
Original Post: Webinar: Data Preparation Essentials for Automated Machine Learning, Nov 29