https://images.unsplash.com/photo-1565018968331-61145555526b?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=1955&q=80IntroductionComputer vision has gained quite a prominence in the industry with the advent of GPUs. In particular object recognition, detection, segmentation plays a pivotal role in a self-driving car 🚘 , automated … [Read more...] about End to End Object Detection theory and implementation.
Machine Learning
Algorithmic Clouds
Photo by Dominik Schröder on UnsplashReading Cambridge Handbook of the Law of Algorithms (edited by Woodrow Barfield, 2021) appeared to me like flying on a long-range aircraft.I departed from good old days of law, enjoyed a 360-degree coverage of social and legal challenges caused by algorithms, and arrived to a brave new world.Here I post an incomplete list of questions the … [Read more...] about Algorithmic Clouds
Applying Machine Learning to Assess Florida’s Climate-Driven Real Estate Risk (part1)
Gathering The DataIn addition to standard real-estate features like bedrooms, bathrooms, area, etc., the data also includes:3 images per property (also contained in the Github repo)2 published flood risk ratings, one from FEMA, and one from First Street’s Flood ScoreEach property is/was listed for sale with a published asking price on realtor.com, as of the 3rd week in … [Read more...] about Applying Machine Learning to Assess Florida’s Climate-Driven Real Estate Risk (part1)
Deep Dive into Neural Networks — Deep Learning for Practitioners; Part 2
Training and Evaluating the NetworkNow comes the interesting part — the learning of the network, we have defined the architecture of the neural network, compiled it with a loss function, an optimizer for the updating weight, and a metric you need to keep track of.For the learning of the network, we need to define when the training should end in this case; the number of epochs, … [Read more...] about Deep Dive into Neural Networks — Deep Learning for Practitioners; Part 2
Decision Trees and Random Forest
By Zachary Galante — Senior Data Science Student at Bryant UniversityPhoto by Peter Fogden on UnsplashIn Machine Learning, a very popular algorithm is the Decision Tree Classifier. In this article, the Banknote dataset will be used to illustrate the capabilities of this model.Decision TreeA decision tree is a basic machine learning algorithm that can be used for classification … [Read more...] about Decision Trees and Random Forest
The NLP Cypher | 02.28.21
Ok, if you own a KIA automobile please read this…👇KIA was apparently hacked with ransomware earlier this month, and the actors want to be paid in full. They are asking for a cool $21 million in BTC. KIA has denied the allegations it was ever hacked although they recently suffered network outages.Read more here.Consequences of the Hack 👀“Kia’s key connected services remain … [Read more...] about The NLP Cypher | 02.28.21
Kubernetes — a Platform approach to AI/ML
by Tom Corcoran, a Solution Architect at Red HatMany organisations are experiencing challenges in creating a streamlined and effective workflow for their Artificial Intelligence and Machine Learning (AI/ML) workloads. Gartner asserted as recently as 2019 that 80% of AI projects are run by practitioners whose talents don’t scale within organisations, ultimately leading to a … [Read more...] about Kubernetes — a Platform approach to AI/ML
Human Voice to Structured Data, My Reflections as a Person Who Stutters on How Voice Assistants…
Have you ever wondered how voice-activated virtual assistants such as Apple’s Siri, Google’s Assistant, and Amazon’s Alexa interact with people who have atypical speech? I have a deeply personal experience with this.On February 24th, Katie Deighton at the Wall Street Journal released a fantastic article that describes a movement for virtual assistants to adapt their algorithms … [Read more...] about Human Voice to Structured Data, My Reflections as a Person Who Stutters on How Voice Assistants…
Robust Trees for Security
Therefore, we propose a cost modeling method to capture the domain knowledge of different feature manipulation cost. For Twitter spam detection, we used high-dimensional box to capture how much an attacker is able to increase and decrease each feature, by four categories: negligible, low, medium, and high cost. This can be generalized to arbitrary constraint-based threat model, … [Read more...] about Robust Trees for Security
Paper Highlights-Challenges in Deploying Machine Learning: a Survey of Case Studies
Production ML is hard. If we can better understand the challenges in deploying ML, we can be better prepared for our next project. That’s why I enjoyed reading Challenges in Deploying Machine Learning: a Survey of Case Studies (on arXiv 18 Jan, 2021) by Paleyes, Urma, and Lawrence. It surveys papers and articles within the last 5 years relevant to the ML deployment process. To … [Read more...] about Paper Highlights-Challenges in Deploying Machine Learning: a Survey of Case Studies