Reinforcement Learning for Personalization at Spotify with Tony Jebara – 609
All right, everyone. Welcome to another episode of the Twilmo AI podcast. I am your host, Sam Charrington. And today I’m joined by Tony Jabara. Tony is a vice president of engineering and head of machine learning at Spotify. Before we get going, be sure to take a moment to hit that subscribe button wherever […]
Exploratory Data Analysis (EDA) with Plotly for Timeseries Demand Forecasting
Let’s have a quick look at exploratory data analysis for demand forecasting using Plotly. Let’s real quick take a look at the time series demand forecasting data set that we’re going to use. This data set is hosted on Kaggle and I created it. It’s essentially a simulation that looks at forecasting the demand of […]
Skin tone and computer vision at Google
Hi, everyone. I’m RL. I’m a PM on Google Research working in RRI and machine perception, particularly perception fairness. And today I’m going to be chatting with you guys about the history of skin tone and computer vision and how Google is now moving needle forward with skin tone detection. So as you can see […]
Research: To be like a bat
Welcome back to Cogax 2021. I’m Christine Foster, CCO at the Allen Turing Institute, and we’re the UK’s Institute for Data Science and Artificial Intelligence. There’s so much happening across the festival, so I’ll mention two of the Turing events. First, Vanessa Lawrence, who’s on the board of the Turing, will join a panel about […]
PyTorch Mobile on Android using C++ (PyTorch Conference 2022 Breakout Session)
Yeah, my name is Joe Bowser. I’m with Adobe. We’re going to talk today about our explorations and using PyTorch mobile on Android. We’re using C++. I’m with the Sensei on device team, our Sensei ML and Furns and efficiency team at Adobe. We go across teams and work on features. So just to give […]
11-785, Fall 22 Lecture 28: Deep Learning in the Real World – Agot.AI (Guest Lecture)
So, everybody, everyone, all seven of you in this room, eight, and hopefully the other 200, one of you can. So, this light lecture of the course, it’s my last lecture. It’s my pleasure and honor to introduce my old friend and previously student at the year Alex Litzinberger, Alex Hussiengier. And after leaving CMU, […]
AI for High-Stakes Decision Making with Hima Lakkaraju – #387
Welcome to the Twimal AI Podcast. I’m your host Sam Charrington. Hey, what is up, good Twimal people? Before we jump into today’s show from our CVPR series, I’d like to share a few quick details about the next great event in our continuing live discussion series. Join us on Wednesday, July 1st for the […]
1-785 Deep Learning Recitation 11: Transformers Part 2
All right, welcome to the Transformers Recitation Part 2. This will be in continuation from part 1 where we coded it from scratch. One thing I’d like to note before we begin is I reviewed the rest of the presentation that I’ve recorded before. And I think I spoke very slowly in terms of my […]
MaDL – Vector Calculus
Let’s now move from differential calculus to vector calculus. That is the differentiation and also integration of vector fields. But in this unit we’ll only cover differentiation. And of course that’s very relevant for lectures like computer vision and the learning because we’re dealing a lot with matrices there. So we need to know how […]
Encoding a Feature Vector for PyTorch Deep Learning (4.1)
Welcome to applications of deep neural networks and PyTorch with Washington University. In this part, we’re going to take a look at how to encode tabular data for PyTorch. Tabular data is data that easily fits in something like Microsoft Excel. It’s not the slickest application of deep neural networks that are often doing computer […]
MaDL – Eigenvalue and Singular Value Decomposition
Many mathematical objects can be better understood by breaking them into parts. An eigen decomposition decomposes a matrix into so-called eigenvectors and eigenvalues.
Faster dataset annotation and model evaluation with Roboflow – Made with TensorFlow.js
Brad is working on a product that empowers developers to build their own computer vision applications, no matter what their skill set or experience may be. Brad: "If I was to describe myself in one word, it's a hacker".
Information Extraction from Natural Document Formats with David Rosenberg – #126
In this episode, I'm joined by David Rosenberg, a data scientist in the office of the CTO at Financial Publisher Bloomberg to discuss his work on extracting data from tables and charts in natural document formats.
Provably Beneficial AI – Stuart Russell | CogX 2019
We're going to talk about a different way of thinking about AI that leads to what we call provably beneficial AI systems.
