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Introduction to Bayesian Deep Learning
Bayes’ theorem is of fundamental importance to the field of data science, consisting of the disciplines: computer science, mathematical statistics, and probability. It is used to calculate the probability of an event occurring based on relevant existing information. Bayesian inference meanwhile leverages Bayes’ theorem to update the probability of... Read more
Enhancing Satellite Imagery Through Super-Resolution
In order to accurately locate crop fields from satellite imagery, it is conceivable that images of a certain quality are required. Although deep learning is notoriously known for being able to pull off miracles, we human beings will have a real field day labeling the data if we cannot... Read more
Recurrent Neural Networks in the Cloud and Edge
Traditionally, neural networks had all their inputs and outputs independent of each other, but in cases, for instance, where it is required to predict the next word of a sentence, information about previous words is essential. Thus, RNN came into existence. Recurrent Neural Network (RNN) is a type of neural... Read more
Image Detection as a Service
Across our two brands, Badoo and Bumble, we have over 500 million registered users worldwide uploading millions of photos a day to our platform. These images provide us with a rich data set from which we derive a wealth of insights. User Profile Information Within our data science team,... Read more
Deep Learning with TensorFlow 2 & PyTorch
I’m greatly honored to be leading the charge on ODSC’s exciting new AI+ Training platform, which brings ODSC’s world-leading ability to provide professional training to data scientists into the digital realm while nevertheless retaining an intimate and engaging experience for attendees.  My Deep Learning with TensorFlow 2 & PyTorch... Read more
Cameras’ biggest recent advancements have come from AI, not sensors and lenses. Over the past couple of years, technology has enabled staggering advances in photography. AI is transforming both the way we shoot photos and how we edit them. As ‘computer vision’ becomes an important part of other new... Read more
Processing Images Through Segmentation Algorithms
Image segmentation is considered one of the most vital progressions of image processing. It is a technique of dividing an image into different parts, called segments. It is primarily beneficial for applications like object recognition or image compression because, for these types of applications, it is expensive to process... Read more
A Look Inside the AI Runtime from Microsoft
Today, I want to wear my software archeology hat, and share with you one story about the AI efforts at Microsoft and how Microsoft built its open-source high-performance AI runtime that is saving the company time and money. A couple of years ago, I decided to create .NET bindings... Read more
Neural Network Optimization
This article is the third in a series of articles aimed at demystifying neural networks and outlining how to design and implement them. In this article, I will discuss the following concepts related to the optimization of neural networks: Challenges with optimization Momentum Adaptive Learning Rates Parameter Initialization Batch... Read more
Deep Learning Talks Coming to the ODSC Virtual Conference April 14-17
Deep learning is an increasingly important of any data scientist’s skillset and any company’s strategies to get ahead. This practice requires a broad knowledge of frameworks, libraries, and algorithms, ranging from neural networks to knowing about hardware capabilities. To help any data scientist stay up-to-date with DL, here are... Read more