YouTube Videos - 2019

In this episode, I explain in plain English 26 Machine Learning and Deep Learning terms that you need to know.

Here you will learn about AI and Machine Learning on Amazon Web Services, from easy high level services to advanced frameworks.

In this episode, I focus on TensorFlow 2.0, the most popular open source library for Machine Learning.

In this episode, I talk about the latest features and I also demo profanity filtering with Transcribe (run for cover!).

In this video, I show you how to build and train a simple Graph Convolutional Network, with the Deep Graph Library and PyTorch.

In this video, I show you how to extract text, tables and forms from images and PDF files.

In this video, I show you how to view labeling statistics, and discuss how to use labeling information for training.

In this video, I show you how to label images, using the new automatic segmentation tool.

In this video, I introduce you to Amazon SageMaker Ground Truth, a fully managed data labeling service, and I show you how to create a private workforce.

In this video, I show you how to create a labeling job, using semantic segmentation as an example.

In this video, I show you how to get started with AWS Inferentia, and Amazon EC2 Inf1 instances.

In this video, I show you how to use Amazon SageMaker Debugger to capture and inspect debugging information for a Keras model.

In this video, I show you how to use Amazon Elastic Inference to save over 75% on GPU inference costs.

In this video, I show you how to use Managed Spot Training to save a ton on money on your training jobs.

In this video, I show you how to use script mode with Amazon SageMaker.

In this video, I show you how to easily deploy a model to a SageMaker endpoint, and to send it data for prediction using the boto3 SDK.

In this video, I show you how to generate music with pretrained models.

In this video, I introduce you to the AWS DeepComposer keyboard! ⭐️⭐️⭐️ Don't forget to subscribe and to enable notifications ⭐️⭐️⭐️ Follow me on…

In this last video, the hyperparameter optimization step is done, and I show you how to visualize and compare model metrics.

In this video, the feature engineering step is complete, and we see the hyperparameter optimization step kicking in!

In this video, we look at the Jupyter notebooks that are auto-generated by Amazon SageMaker AutoPilot after the data analysis step.

In this video, I show how you to fire up an AutoML job with Amazon SageMaker Autopilot.

Amazon Transcribe Medical is a machine learning service that makes it easy to quickly create accurate transcriptions from medical consultations between…

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Description: No, Amazon Web Services is not only Linux territory! It’s actually quite easy to run your favorite BSD OS in the Cloud and we’ll show you…

Going through every single feature added since launch at AWS re:Invent 2017!

An overview of Machine Learning services on AWS September 2018 - Julien Simon — a video by Julien Simon on AI, ML, and small language models.

Présenté par Julien Simon, Global Technical Evangelist AI/ML, AWS. Amazon SageMaker est un service managé qui aide les développeurs et les data…

Car batteries and charger: https://www.amazon.com/Klions-1100mah-Battery-1Charger-WLtoys/dp/B07QRSSVH7/ (or equivalent)

Easy setup, no problem at all. Instructions here: https://aws.amazon.com/deepracer/getting-started/

Téléchargez la présentation : https://chilp.it/1dc90a5 Retrouvez l'intégralité des sessions de l'AWS Summit Paris 2019…

Téléchargez la présentation : https://chilp.it/dc2bbf0 Retrouvez l'intégralité des sessions de l'AWS Summit Paris 2019…

Lviv Innovation in AWS Cloud Solutions MeetUP Julien Simon. Amazon Global Artificial Intelligence & Machine Learning.

Lviv Innovation in AWS Cloud Solutions MeetUP Julien Simon. Amazon Global Artificial Intelligence & Machine Learning.

Lviv Innovation in AWS Cloud Solutions MeetUP Julien Simon. Amazon Global Artificial Intelligence & Machine Learning.