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TensorFlow Lite: Reference app gallery (TF Dev Summit '20)

TFLite developed more than 10 example apps that show not only how to use the model, but also the E2E code the developer will need to write. This video demonstrates three of the latest ones, MobileBert Q&A, Pose Estimation, and Style transfer. Speakers: Lu Wang – Software Engineer Ewa Matejska – Technical Program Manager Resources: […]
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Applications of Deep Neural Networks Class Session 4

The fourth class presents classification and regression in greater detail. This includes grid search, cross validation, holdout. Jupyter notebooks, data files, and other information can be found at: https://sites.wustl.edu/jeffheaton/t81-558/ Source of this machine learning/AI Video
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Ilkka Korhonen Interview – Physiology-Based Models for Fitness and Training w/ Firstbeat

In this episode i’m joined by Ilkka Korhonen, Vice President of Technology at Firstbeat, a company whose algorithms are embedded in fitness watches from companies like Garmin and Suunto and which use your heartbeat data to offer personalized insights into stress, fitness, recovery and sleep patterns. We cover a ton about Firstbeat in the conversation, […]
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Overview of Keynote and Technologies from Day 1 of the GPU Tech Conference (GTC)

I am virtually attending the 2020 GPU Technology Conference (GTC) this week. In this video, I cover highlights from the keynote and new announcements from NVIDIA. I also cover the technology topics that I will be covering in follow up videos. Keynote presentation online: https://www.youtube.com/watch?v=Dw4oet5f0dI GTC2020: https://www.nvidia.com/en-us/gtc/ My Github REPO for GTC2020: https://github.com/jeffheaton/present/tree/master/youtube/gtc-2020 ** Follow […]
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Naver Labs at CES2019

Sam previews the 2019 Innovation Award winning Ambidex robot from Naver Labs. YouTube Source for this AI Video
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Philipp Berens: Towards hybrid models of retinal circuits

Philipp Berens: Towards hybrid models of retinal circuits – integrating biophysical realism, anatomical constraints and predictive performance This is the live stream of the “Machine Learning in Science” Conference 2020. The conference is held by the Cluster of Excellence “Machine Learning: New Perspectives for Science”, University of Tübingen, Germany. Conference program: https://uni-tuebingen.de/en/165313 Follow @ml4science on […]
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Measuring Performance Under Pressure Using ML with Lotte Bransen – TWIML Talk #296

Today we are joined by Lotte Bransen, Scientific Researcher at SciSports. With a background in mathematics, econometrics and soccer, Lotte has honed her research on analytics of the game and its players. More specifically, using trained models to understand the impact of mental pressure on a player’s performance. In this episode, Lotte discusses: Her latest […]
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Next Gen Infrastructure & Industry 4.0: Intelligent automation: Driving industry transformation

Next Gen Infrastructure & Industry 4.0: Intelligent automation: Driving industry transformation Emerging technologies like AI, robotic process automation and business process optimisation have the capacity to revolutionise business services, enhance digitisation and build resilience. This session explores how intelligent automation technologies are already being used, and how the convergence of industry 4.0 technologies is making […]
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Optimize your TensorFlow Lite models | Session

Mobile and embedded devices have limited computational resources, so it’s important to keep your application resource efficient. In this Session, we cover performance and model optimization tools, techniques, best practices that you can use to improve your model performance, and ensure that your model runs well within these constraints. Resources: Tensorflow Lite → https://goo.gle/2QCwBjG Tensorflow […]
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Introduction to Neural Networks for Java(Class 9/16, Part 3/3) incremental pruning

Learn Neural Net Programming: http://www.heatonresearch.com/course/intro-neural-nets-java In class session 9, part 3 we introduce incremental pruning for neural networks. This works by increasing the hidden neuron count until an optimal count is reached. Artificial intelligence online course presented by Jeff Heaton, Heaton Research. Source of this machine learning/AI Video
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Managing Deep Learning Experiments with Lukas Biewald – TWIML Talk 295

Today we are joined by Lukas Biewald, CEO and Co-Founder of Weights & Biases. Lukas, previously CEO and Founder of Figure Eight (CrowdFlower), has a straightforward goal: provide researchers with SaaS that is easy to install, simple to operate, and always accessible. Seeing a need for reproducibility in deep learning experiments, Lukas founded Weights & […]
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Delivering a national AI strategy: Global perspectives | CogX 2020

Delivering a national AI strategy: Global perspectives Ott Velsberg – Government Chief Data Officer – Estonian Ministry of Economic Affairs & Communications Sana Khareghani – Head – UK Office for Artificial Intelligence Dr Zhenzhi Chng – Director (National AI Office) – Smart Nation and Digital Government Office – Singapore Samuel Marleau Ouellet – Director, Artificial […]
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09 Wilcoxon

Source of this “Tübingen Machine Learning” AI Video
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機械学習を用いたコンピュータービジョンの基本(機械学習ゼロからヒーローへ 第二部)

機械学習ゼロからヒーローへの第二部では、画像に写っているものをコンピューターに認識させる機械学習についてチャールズが解説します。 リンク先でコンピュータビジョンのコードを実行してみましょう!→ https://goo.gle/34cHkDk コーディング・テンサーフローのプレイリスト → https://goo.gle/Coding-TensorFlow テンサーフローをチャンネル登録 → https://goo.gle/TensorFlow Source of this TensorFlow AI Video
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Augmenting Your Kaggle Model with Features that Others Share

Other people release features (new columns to add to your model) frequently in a Kaggle competition. It is very necessary to be able to incorporate these quickly into your own competition. My Kaggle utilities: https://github.com/jeffheaton/jh-kaggle-util Source of this machine learning/AI Video
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#TWIMLfest – Lightning Sessions #1

In this session we invite any and all from expert to beginner to share their ML experience, knowledge and projects. Presentations will be 2 minutes, focused on … YouTube Source for this AI Video