107

22:20

Setting Up CUDA, CUDNN, Keras, and TensorFlow on Windows 11 for GPU Deep Learning

Complete walkthrough of installing TensorFlow/Keras with GPU support on Windows 11. We make use of a “pip install” rather than conda, to ensure that we get the latest version of TensorFlow. This requires installing Visual C++, CUDA, CuDNN, as well as the Python libraries. Guide: https://github.com/jeffheaton/t81_558_deep_learning/blob/master/install/manual_setup2.ipynb 0:54 Installation Guides 2:03 Step 1: NVIDIA Video Driver […]

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29:08

Proximal Policy Optimization is Easy with Tensorflow 2 | PPO Tutorial

Proximal Policy Optimization (PPO) has emerged as a powerful on policy actor critic algorithm. You might think that implementing it is difficult, but in fact tensorflow 2 makes coding up a PPO agent relatively simple. We’re going to take advantage of my PyTorch code for this, as it serves as a great basis to expand […]

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49

12:38

MirroredStrategy demo for distributed training

Google Cloud Developer Advocate Nikita Namjoshi demonstrates how to get started with distributed training on Google Cloud. Learn how to distribute training across multiple GPUs within a managed Jupyter Lab environment. Intro to distributed training → https://goo.gle/3FolcIz Creating and managing GCP projects → https://goo.gle/3mDZ4m7 Vertex AI → https://goo.gle/3FzfmUU Cloud Storage Quickstart → https://goo.gle/3qsNWcN Notebook Executor […]

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215

24:19

A friendly introduction to distributed training (ML Tech Talks)

Google Cloud Developer Advocate Nikita Namjoshi introduces how distributed training models can dramatically reduce machine learning training times, explains how to make use of multiple GPUs with Data Parallelism vs Model Parallelism, and explores Synchronous vs Asynchronous Data Parallelism. Mesh TensorFlow → https://goo.gle/3sFPrHw Distributed Training with Keras tutorial → https://goo.gle/3FE6QEa GCP Reduction Server Blog → […]

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91

06:56

Choose an object detection model architecture for Raspberry Pi

In machine learning, there’s often a trade-off between accuracy and inference speed. In this video, we’ll compare models in the EfficientDet-Lite model family running on Raspberry Pi to help you choose the one that best meets your needs. 00:00 Introduction 00:14 Relationship between accuracy and inference speed 00:58 EfficientDet-Lite for edge-devices 1:41 Comparing the EfficientDet-Lite […]

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181

05:42

Construire un classifieur d'images (Coding TensorFlow en français)

This video is available in English: https://goo.gle/33Kxmc3 Dans la quatrième partie de l’apprentissage automatique “Zero to Hero”, Catherine décrit la construction d’un classifieur d’images pour le jeu: pierre, papier et ciseaux. Dans le premier épisode, nous avons présenté un scénario de pierre, papier et ciseaux; et discuté de la difficulté d’écrire un code pour détecter […]

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792

05:32

Google Colab features you may have missed

Nate from the Google Colab team shares lesser known, powerful features in Google Colaboratory that will allow you to dynamically explore Pandas DataFrames, view your history to see past commands you ran in your notebook, and boost your productivity. Any features you want to highlight? Let us know in the comments! 00:00 Introduction 00:08 Overview […]

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90

14:44

Simplified Machine Learning on mobile, browsers, and edge devices with on-device ML

Explore solutions from Google to train and run machine learning models on phones, mobile devices, browsers, and edge devices. Join us as we discuss turnkey API-based solutions for text recognition, NLP, pose detection, translation support, and more. We’ll also examine new, improved features of TensorFlow Lite (TFLite) and walk through a demo. Resources: Deploy machine […]

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198

12:10

Train a custom object detection model using your data

Learn how to train a custom object detection model for Raspberry Pi to detect less common objects like versions of a logo using your own collection of data. 00:00 Introduction 00:49 The 3 steps of training a custom model 01:24 Step 1: Create a training dataset 04:01 Step 2: Train a custom model with TensorFlow […]

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41

09:56

SingularityNET: SingularityNET MNIST Tutorial

This tutorial shows how to integrate any new AI code or system with the SingularityNET architecture. The tutorial uses the Tensorflow MNIST AI code from the Tensorflow tutorial, Deep MNIST for Experts, as an example. See: https://www.tensorflow.org/get_started/mnist/pros However, the tutorial focuses on the integration of Artificial Intelligence, in general. So a deep understanding of Tensorflow […]

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370

10:12

Introduction to object detection on Raspberry Pi

In the first episode of Machine Learning for Raspberry Pi, learn how to download a pre-trained TensorFlow Lite object detection model and deploy it to your Raspberry Pi. This model can be used to recognize general objects such as an apple, a television, or a car. 00:00 Welcome to the Machine Learning for Raspberry Pi […]

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863

04:46

Two Minute Papers: No Such Thing As Artificial Intelligence | Two Minute Papers #60

What is happening with the neural networks in this video? You’ll find the answers in these videos: 1. How Does Deep Learning Work? – https://www.youtube.com/watch?v=He4t7Zekob0&index=5&list=PLujxSBD-JXglGL3ERdDOhthD3jTlfudC2 2. Overfitting and Regularization For Deep Learning – https://www.youtube.com/watch?v=6aF9sJrzxaM&index=18&list=PLujxSBD-JXglGL3ERdDOhthD3jTlfudC2 In this episode, we discuss the perils of debating whether different existing techniques can be deemed artificial intelligence or not. ____________________ […]

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25:40

[ML News] DeepMind tackles Math | Microsoft does more with less | Timnit Gebru launches DAIR

#mlnews #deepmind #ai The most trusted model in News! Get started with Weights & Biases here: https://wandb.me/yannic (it’s free forever for personal use) OUTLINE: 0:00 – Intro 0:15 – Sponsor: Weights & Biases 3:10 – DeepMind tackles fundamental math 6:45 – Microsoft focuses on scaling effectively and efficiently 10:15 – NeurIPS Anthology Visualization 13:30 – […]

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230

14:08

Apple's M1 Pro and M1 Max are faster than Google Colab (machine learning speed test)

Let’s see how Apple’s new M1 Pro and M1 Max deal with various machine learning workloads. Blog post with results – https://www.mrdbourke.com/m1-pro-m1-max-machine-learning-speed-test-comparison Code on GitHub – https://github.com/mrdbourke/m1-machine-learning-test Setup your M1 Mac for machine learning video – https://youtu.be/_1CaUOHhI6U Links: Learn ML (beginner-friendly courses I teach) – https://www.mrdbourke.com/ml-courses/ ML courses/books I recommend – https://www.mrdbourke.com/ml-resources/ Read my novel […]

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122

13:01

Setup Apple M1 Pro, M1 Max MacBook Pro for Machine Learning in 13-minutes (also works for M1)

How to get your Apple M1 Pro, M1 Max or M1 MacBook Pro setup for data science and machine learning. In this video, we install Homebrew and Miniforge3 to create a Conda environment containing pandas, NumPy, Scikit-Learn, Matplotlib, Jupyter and TensorFlow. We’ll also setup TensorFlow to leverage the GPU on the new M1 chips. Step […]

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584

01:10

Help Protect the Great Barrier Reef with Machine Learning

We are excited to announce a TensorFlow-sponsored Kaggle challenge to locate and identify harmful crown-of-thorns starfish (COTS), as part of a broader partnership between the Commonwealth Scientific and Industrial Research Organization (CSIRO) and Google, to help protect coral reefs everywhere. Join the challenge today at https://goo.gle/reef Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow Source of […]

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214

29:09

[ML News] OpenAI removes GPT-3 waitlist | GauGAN2 is amazing | NYC regulates AI hiring tools

#mlnews #gaugan #gpt-3 Your weekly dose of ML News! More GauGAN images here: https://drive.google.com/drive/folders/1tG1rpxP_mnspB1MWi9VZGScw5R-hxUdm?usp=sharing OUTLINE: 0:00 – Intro 0:20 – Sponsor: Weights & Biases 2:20 – OpenAI’s removes GPT-3 Waitlist 4:55 – NVIDIA releases GauGAN2 Webapp 9:45 – Everyday Robots tackles real-life tasks 12:15 – MetNet-2: 12-hour Rain Forecasting 14:45 – TinyML Dog Bark Stopper […]

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265

06:09

卷积神经网络简介（机器学习从零到一第三集）

在第三集的系列视频中，费颖会讨论卷积神经网络，以及为什么它们在计算机视觉中得到了广泛的应用。 卷积是一个图像过滤器。它可以用来提取输入图像中具有共性的特征。 在此视频中，你将通过处理一张输入图像，看能否从中提取特征，来了解它的工作原理。 卷积简介 → https://goo.gle/2m07asM 观看更多TensorFlow编码视频 → https://goo.gle/2Y43cN4 订阅 TensorFlow 频道 → https://goo.gle/2WtM7Ak Source of this TensorFlow AI Video

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12:20

Building fair, ethical, and responsible AI with the Responsible AI Toolkit

Responsible AI aims to address a wide range of ethical concerns related to the use of AI. As a developer, it can be hard to know where to start. This talk will introduce Google’s Responsible AI Toolkit and do a deep-dive on two practical model analysis tools you can use to stress-test your model for […]

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31

05:05

Simplified distributed training with tf.distribute parameter servers

Learn about a new tf.distribute strategy, ParameterServerStrategy, which enables asynchronous distributed training in TensorFlow, along with its usage with Keras APIs and custom training loop. If you have models with large embeddings or an environment with preemptible machines, this approach lets you scale your training much more easily with minimum code changes. Resources: Distributed training […]

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303

07:06

Machine learning tools from Google 2021 | Keynote

Explore an overview of the developments in the machine learning ecosystem at Google that can be applied across your ML powered apps, from hobby projects to cutting-edge research. Speaker: Nadav Eiron (VP, Engineering) Watch all Google’s Machine Learning Virtual Community Day sessions → https://goo.gle/mlcommunityday-all Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #MLCommunityDay product: TensorFlow – […]

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03:32

How Machine Learning tools at Google made AlphaFold possible | Keynote

The DeepMind team shares how JAX and TPUs have been used to push state-of-the-art research in protein folding and how it made AlphaFold possible. Speaker: Tim Green (Research Engineer, DeepMind) Watch all Google’s Machine Learning Virtual Community Day sessions → https://goo.gle/mlcommunityday-all Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #MLCommunityDay product: TensorFlow – General; event: ML […]

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329

04:33

Incredible things your community is creating with TensorFlow.js – #MadeWithTFJS

Usage of Machine Learning in JavaScript has grown exponentially since 2020 and is expected to continue. Check out just a few of our community highlights to see what people are making from all around the world. From self driving cars to motion captured avatars, we have it all, and it runs with a single click […]

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157

03:41

State-of-the-art Machine Learning research with Google tools | Keynote

Explore how the Google ML ecosystem tools are used for state-of-the-art research. Speaker: Laurence Moroney (AI Advocate) Watch all Google’s Machine Learning Virtual Community Day sessions → https://goo.gle/mlcommunityday-all Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #MLCommunityDay product: TensorFlow – General; event: ML Community Day 2021; fullname: Laurence Moroney; re_ty: Publish; Source of this TensorFlow AI […]

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