[unable to retrieve full-text content]This is a collection of introductory posts which present a basic overview of neural networks and deep learning. Start by learning some key terminology and gaining an understanding through some curated resources. Then look at summarized important research in the field before looking at a pair of concise case studies.
Original Post: Deep Learning and Neural Networks Primer: Basic Concepts for Beginners
[unable to retrieve full-text content]Big Squid offers a Predictive Analytics Platform that uses automated Machine Learning to take your Looker investment from real-time data and insights to forward-looking action and impact. Learn more on Aug 24.
Original Post: Build a Path to Predictive Analytics with Big Squid & Looker, Aug 24
[unable to retrieve full-text content]This is a fast paced, vendor agnostic, technical overview of the Big Data landscape, targeted towards people who want to understand the emerging world of Big Data. Use code KDNUGGETS to save.
Original Post: Big Data Bootcamp, Denver, Sep 8-10
[unable to retrieve full-text content]Seeking a full-time, tenure-track appointment in the Department of Global Korean Studies at Sogang’s School of Integrated Knowledge.
Original Post: Sogang University: Data Scientist in Korean Studies
[unable to retrieve full-text content]Read “Analyst of the Future” guidebook to discover 3 emerging analyst roles and what they encompass, 4 trends transforming the world of data, and more.
Original Post: The Role of the Data Analyst in a Predictive Era
[unable to retrieve full-text content]The recent but noticeable shift from CPUs to GPUs is mainly due to the unique benefits they bring to sectors like AdTech, finance, telco, retail, or security/IT . We examine where GPU databases shine.
Original Post: The Rise of GPU Databases
[unable to retrieve full-text content]The first winter occurred in the 1970s, followed by another one in 1980s for some reason or the other, but majorly due to less resources. I agree that there have been many major breakthroughs but here’s my attempt to illustrate the timeline of major events…
Original Post: A New Beginning to Deep Learning
[unable to retrieve full-text content]I am writing this article to show you the basics of using Instagram in a programmatic way. You can benefit from this if you want to use it in a data analysis, computer vision, or any other cool project you can think of.
Original Post: A Guide to Instagramming with Python for Data Analysis
[unable to retrieve full-text content]Also 37 Reasons why your #NeuralNetwork is not working; Making Predictive Model Robust: Holdout vs Cross-Validation.
Original Post: Top KDnuggets tweets, Aug 09-15: #Tensorflow tutorials and best practices; Top Influencers for #DataScience
[unable to retrieve full-text content]This live webinar (Aug 22) will discuss the impact that the notebook experience has had on data science, and how JupyterLab – the next generation data science IDE – has evolved from the classic notebooks.
Original Post: From Notebooks to JupyterLab – The Evolution of Data Science IDEs