In this contributed article, graphic designer and content writer, Erika Ballo delves into some emerging tools and frameworks in AI, comparing their strengths, usability, and ideal use cases.
Book Review: Deep Learning with TensorFlow 2 and Keras
August 4, 2020 by 4 Comments
If you’re a data scientist who has been wanting to break into the deep learning realm, here is a great learning resource that can guide you through this journey. It’s pretty much an all-inclusive resource that includes all the popular methodologies upon which deep learning depends: CNNs, RNNs, RL, GANs, and much more. The glue that makes it all work is represented by the two most popular frameworks for deep learning pratcitioners, TensorFlow and Keras.
Interview: Global Technology Leader PNY
July 13, 2020 by Leave a Comment
The following whitepaper download is a reprint of the recent interview with our friends over at PNY to discuss a variety of topics affecting data scientists conducting work on big data problem domains including how “Big Data” is becoming increasingly accessible with big clusters with disk-based databases, small clusters with in-memory data, single systems with in-CPU-memory data, and single systems with in-GPU-memory data. Answering our inquiries were: Bojan Tunguz, Senior System Software Engineer, NVIDIA and Carl Flygare, NVIDIA Quadro Product Marketing Manager, PNY.
Book Review: Python Machine Learning – Third Edition by Sebastian Raschka, Vahid Mirjalili
February 19, 2020 by Leave a Comment
I had been looking for a good book to recommend to my “Introduction to Data Science” classes at UCLA as a text to use once my class completes … sort of the next step after learning the basics. That’s why I was looking forward to reviewing the new 3rd edition of the widely acclaimed title “Python Machine Learning” by Sebastian Raschka, Vahid Mirjalili. The book is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a useful resource you’ll keep coming back to as you fill up your data science toolbox.
insideBIGDATA Guide to Optimized Storage for AI and Deep Learning Workloads
September 10, 2019 by Leave a Comment
This new technology guide from DDN shows how optimized storage has a unique opportunity to become much more than a siloed repository for the deluge of data constantly generated in today’s hyper-connected world, but rather a platform that shares and delivers data to create competitive business value. The intended audience for this important new technology guide includes enterprise thought leaders (CIOs, director level IT, etc.), along with data scientists and data engineers who are a seeking guidance in terms of infrastructure for AI and DL in terms of specialized hardware. The emphasis of the guide is “real world” applications, workloads, and present day challenges.
DarwinAI Generative Synthesis Platform and Intel Optimizations for TensorFlow Accelerate Neural Networks
July 24, 2019 by Leave a Comment
DarwinAI, a Waterloo, Canada startup creating next-generation technologies for Artificial Intelligence development, announced that the company’s Generative Synthesis platform – when used with Intel technology and optimizations – generated neural networks with a 16.3X improvement in image classification inference performance. Intel shared the optimization results in a recently published solution brief.
DarwinAI Generative Synthesis* Platform and Intel® Optimizations for TensorFlow* Accelerate Neural Networks
July 20, 2019 by Leave a Comment
DarwinAI, a Waterloo, Canada startup creating next-generation technologies for Artificial Intelligence development, announced that the company’s Generative Synthesis platform – when used with Intel technology and optimizations – generated neural networks with a 16.3X improvement in image classification inference performance. Intel shared the optimization results in this recently published solution brief. The complexity of deep […]
Book Review: Learning TensorFlow
January 9, 2018 by Leave a Comment
Deep Neural Networks (DNNs), upon which deep learning is based, are trained with large amounts of data, and can solve complex tasks with unprecedented accuracy. TensorFlow is a leading open source software framework that helps you build and train neural networks. Here’s a nice resource to help you kick-start your use of TensorFlow – “Learning TensorFlow” by Tom Hope, Yehezkel S. Resheff and Itay Leider.
Large Scale Deep Learning with TensorFlow
November 11, 2017 by Leave a Comment
In this video presentation from the Spark Summit 2016 conference in San Francisco, Google’s Jeff Dean examines large scale deep learning with the TensorFlow framework. Jeff joined Google in 1999 and is currently a Google Senior Fellow.
TensorFlow Tutorial – Simple Linear Model
October 21, 2017 by Leave a Comment
In this excellent tutorial video presentation below, Magnus Erik Hvass Pedersen demonstrates the basic workflow of using TensorFlow with a simple linear model. You should be familiar with basic linear algebra, Python and the Jupyter Notebook editor. It also helps if you have a basic understanding of Machine Learning and classification.
