In this episode, I go through our November announcements on all AI/ML services. This is a great way to catch up before AWS re:Invent starts⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️For more content:* AWS blog: https://aws.amazon.com/blogs/aws/auth...* Medium blog: https://julsimon.medium.com* YouTube: https://youtube.com/juliensimonfr * Podcast: http://julsimon.buzzsprout.com * Twitter https://twitter.com/@julsimon

AWS AI & Machine Learning

Episode 20: pre:Invent!

In this episode, I go through our latest announcements on Amazon Polly, Amazon Rekognition, Amazon Lex, Amazon Personalize, and Amazon SageMaker Ground Truth. I demo how to use a Lex chatbot for search queries on Kendra.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Rekognition blog post: https://aws.amazon.com/blogs/media/streamline-media-analysis-tasks-with-amazon-rekognition-video/Kendra blog post: https://aws.amazon.com/blogs/aws/reinventing-enterprise-search-amazon-kendra-is-now-generally-available/SageMaker Ground Truth blog post: https://aws.amazon.com/blogs/aws/new-label-3d-point-clouds-with-amazon-sagemaker-ground-truth/For more content:* AWS blog: https://aws.amazon.com/blogs/aws/auth...* Medium blog: https://medium.com/@julsimon * YouTube: https://youtube.com/juliensimonfr * Podcast: http://julsimon.buzzsprout.com * Twitter https://twitter.com/@julsimon

Episode 19: AWS News

In this episode, I go through our latest announcements on Amazon Forecast, Amazon Code Guru, Amazon Transcribe, and the AWS Deep Learning Containers. I demo real-time profanity filtering with Transcribe (run for cover), and Elastic Inference with TensorFlow and SageMaker.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️For more content:* AWS blog: https://aws.amazon.com/blogs/aws/auth...* Medium blog: https://medium.com/@julsimon * YouTube: https://youtube.com/juliensimonfr * Podcast: http://julsimon.buzzsprout.com * Twitter https://twitter.com/@julsimon

Episode 18: AWS News

In this episode, I go through our latest announcements on AWS Amazon Augmented AI, Amazon SageMaker Studio, Amazon Sagemaker, and PyTorch.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️AWS blog posts mentioned in the podcast:* https://aws.amazon.com/blogs/machine-learning/announcing-availability-of-inf1-instances-in-amazon-sagemaker-for-high-performance-and-cost-effective-machine-learning-inference/* https://aws.amazon.com/blogs/aws/announcing-torchserve-an-open-source-model-server-for-pytorch/ For more content:* AWS blog: https://aws.amazon.com/blogs/aws/auth...* Medium blog: https://medium.com/@julsimon * YouTube: https://youtube.com/juliensimonfr * Podcast: http://julsimon.buzzsprout.com * Twitter https://twitter.com/@julsimon

Episode 17: AWS news

In this episode, I go through our latest announcements on AWS Textract, Amazon Polly. AWS DeepLens, Amazon SageMaker, and the AWS Deep Learning Composers. A couple of small demos are included.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️For more content:* AWS blog: https://aws.amazon.com/blogs/aws/auth...* Medium blog: https://medium.com/@julsimon * YouTube: https://youtube.com/juliensimonfr * Podcast: http://julsimon.buzzsprout.com * Twitter https://twitter.com/@julsimon

Episode 16: AWS news

In this episode, I go through our latest announcements on AWS DeepComposer, Amazon Transcribe Medical, and Amazon Personalize.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Additional resources mentioned in the podcast:AWS DeepComposer blog post: https://aws.amazon.com/blogs/aws/aws-deepcomposer-now-generally-available-with-new-features/ Amazon Transcribe Medical demo: https://www.youtube.com/watch?v=_FoA5DZn7M8Amazon Personalize blog post: https://aws.amazon.com/blogs/machine-learning/introducing-recommendation-scores-in-amazon-personalize/For more content:AWS blog: https://aws.amazon.com/blogs/aws/author/julsimonMedium blog: https://medium.com/@julsimon YouTube: https://youtube.com/juliensimonfr Podcast: http://julsimon.buzzsprout.com Twitter https://twitter.com/@julsimon

Episode 15: AWS news

In this episode, I go through our latest announcements on Amazon Forecast, Amazon Personalize, Amazon SageMaker Ground Truth, AWS Deep Learning AMIs, and Amazon Elastic Inference.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Additional resources mentioned in the podcast:AWS Solutions: https://aws.amazon.com/solutions/Amazon SageMaker Ground Truth end to end demo: https://www.youtube.com/watch?v=oEcH8amMcT8Amazon Elastic Inference: https://aws.amazon.com/blogs/machine-learning/category/artificial-intelligence/amazon-elastic-inference/This podcast is also available in video at https://youtu.be/H8VjSI6Czy8 For more content:AWS blog: https://aws.amazon.com/blogs/aws/author/julsimonMedium blog: https://medium.com/@julsimon YouTube: https://youtube.com/juliensimonfr Podcast: http://julsimon.buzzsprout.com Twitter https://twitter.com/@julsimon

Episode 14: AWS news

In this episode, I focus on Amazon Kendra, an enterprise search service powered by machine learning... but you don't need any ML skills to set it up and use it! I show you how to create an index, add data sources, and then I run queries using the AWS console and the AWS CLI. ⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️https://aws.amazon.com/kendra/This podcast is also available in video at https://youtu.be/sd6Ydg0wAPsFor more content, follow me on:* Medium https://medium.com/@julsimon* Twitter https://twitter.com/@julsimon

Episode 13: Amazon Kendra special

In this episode, I go through our latest announcements on Amazon Transcribe, Amazon Rekognition, Amazon Forecast and the Deep Learning Containers. I do a couple of demos (redacting personal information in text transcripts, and extracting text from videos). Finally, I share a couple of SageMaker videos that I recently recorded.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Additional resources mentioned in the podcast:Amazon Transcribe blog post: https://aws.amazon.com/blogs/aws/now-available-in-amazon-transcribe-automatic-redaction-of-personally-identifiable-information/Amazon Rekognition Video code: https://gitlab.com/juliensimon/aws/-/blob/master/AmazonAI/rekognitionvideo/textinimage.py DeepAR research paper: https://arxiv.org/abs/1704.04110Train with Amazon SageMaker on your local machine: https://www.youtube.com/watch?v=K3ngZKF31mcAmazon SageMaker Studio Deep Dive: https://www.youtube.com/watch?v=pGhn8Ax8QmQ This podcast is also available in video at https://youtu.be/czngW9WkjxwFor more content, follow me on:Medium https://medium.com/@julsimonTwitter https://twitter.com/@julsimon

Episode 12: AWS news and demos

In this episode, I talk about XGBoost 1.0, a major milestone for this very popular algorithm. Then, I discuss the three options you have for running XGBoost on Amazon SageMaker: built-in algo, built-in framework, and bring your own container. Code included, of course!⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Additional resources mentioned in the podcast:* XGBoost built-in algo: https://gitlab.com/juliensimon/ent321* XGBoost built-in framework: https://gitlab.com/juliensimon/dlnotebooks/-/blob/master/sagemaker/09-XGBoost-script-mode.ipynb * BYO with Scikit-learn: https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.ipynb * Deploying XGBoost with mlflow: https://youtu.be/jpZSp9O8_ew * New model format: https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html* Converting pickled models: https://github.com/dmlc/xgboost/blob/master/doc/python/convert_090to100.py This podcast is also available in video at https://youtu.be/w0F4z0dMdzI.For more content, follow me on:* Medium https://medium.com/@julsimon* Twitter https://twitter.com/@julsimon

Episode 11: XGBoost special

In this episode, I cover new features on Amazon Personalize (recommendation & personalization), Amazon Polly (text to speech), and Apache MXNet (Deep Learning). I also point out new notebooks for Amazon SageMaker Debugger, a couple of recent videos that I recorded, and an upcoming SageMaker webinar.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Additional resources mentioned in the podcast:* Amazon Polly Brand Voice: https://aws.amazon.com/blogs/machine-learning/build-a-unique-brand-voice-with-amazon-polly/* Amazon SageMaker Debugger notebooks: https://github.com/awslabs/amazon-sagemaker-examples/blob/master/sagemaker-debugger* Numpy for Apache MXNet: https://medium.com/apache-mxnet/a-new-numpy-interface-for-apache-mxnet-incubating-dbb4a4096f9f* Automating Amazon SageMaker workflows with AWS Step Functions: https://www.youtube.com/watch?v=0kMdOi69tjQ* Deploying Machine Learning Models with mlflow and Amazon SageMaker: https://www.youtube.com/watch?v=jpZSp9O8_ew* SageMaker webinar on February 27th: https://pages.awscloud.com/AWS-Online-Tech-Talks_2020_0226-MCL.htmlThis podcast is also available in video: https://youtu.be/KE83Aw6UvHk For more content, follow me on:* Medium https://medium.com/@julsimon * Twitter https://twitter.com/@julsimon

Episode 10: AWS news and demos

In this episode, I have a chat with Leo Souquet, a Data Scientist and the co-founder of the Data Science Tech Institute (https://www.datasciencetech.institute). DSTI trains Data Scientists and Data Engineers, and we chat about those two roles, their respective skills, how they’re related, and why you need both on your team to build successful projects. Much to my sorrow, Leo also convincingly explains why you have to learn math to build the best models.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️This podcast is also available in video at https://youtu.be/llSjMi-Vjvk.For more content, follow me on:- Medium: https://medium.com/@julsimon- Twitter: https://twitter.com/julsimon

Episode 9

In this episode, I have a chat with Ségolène Dessertine-Panhard, a Data Scientist with the AWS Machine Learning Solutions Lab (https://aws.amazon.com/ml-solutions-lab/). As she spends her time working on customer projects, we talk about ML in the trenches: framing problems, building datasets, picking algos, deploying to production, and more.⭐️⭐️⭐️ Don&apos;t forget to subscribe to be notified of future episodes ⭐️⭐️⭐️This podcast is also available in video at https://youtu.be/74LwQP9oKU4For more content, follow me on:- Medium: https://medium.com/@julsimon- Twitter: https://twitter.com/julsimon

Episode 8

In this episode, I have a chat with Francesco Pochetti, a Data Scientist who worked on Amazon Kindle for 4 years. He's also an AWS Machine Learning Hero. We talk about real life ML, how to deal with business stakeholders, why model explainability is so important, and more.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Francesco's Twitter: @Fra_PochettiFrancesco's blog: https://francescopochetti.com/This podcast is also available in video at https://youtu.be/DQh9FQxwvhIFor more content, follow me on:* Medium: https://medium.com/@julsimon* Twitter: https://twitter.com/julsimon

Episode 7

In this episode, I have a chat with Cosmin Catalin Sanda, a Data Science Engineer for AudienceProject (https://www.audienceproject.com). We talk about real life ML, what it takes for ML projects to be successful (experimentation, agility, intuition, etc.), how SageMaker helps, and more.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Cosmin's Twitter: https://twitter.com/cosminsandaCosmin's blog: https://cosminsanda.com/ Apache MXNet User Group in Copenhagen: https://www.meetup.com/meetup-group-bdEUVQHL/This podcast is also available in video at https://youtu.be/YqRd4Gh9a98For more content, follow me on:* Medium: https://medium.com/@julsimon* Twitter: https://twitter.com/julsimon

Episode 6

This podcast is hosted by Julien Simon, Global Evangelist for AI and Machine Learning at Amazon Web Services. It covers everything you need to know about AI and ML on AWS: new features, demos, conversation and more! The podcast is hosted at https://julsimon.buzzsprout.com, and is also available on YouTube at https://bit.ly/368Iz7g.

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AWS AI & Machine Learning

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