AWS AI & Machine Learning Podcast

Episode 20: pre:Invent! Dec 01, 2020

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
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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

Episode 19: AWS News Jun 24, 2020

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.
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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 18: AWS News May 22, 2020

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.
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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 May 01, 2020

In this episode, I go through our latest announcements on AWS Amazon Augmented AI, Amazon SageMaker Studio, Amazon Sagemaker, and PyTorch.
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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 16: AWS news Apr 20, 2020

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.
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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 15: AWS news Apr 07, 2020

In this episode, I go through our latest announcements on AWS DeepComposer, Amazon Transcribe Medical, and Amazon Personalize.

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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=_FoA5DZn7M8
Amazon 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/julsimon
Medium blog: https://medium.com/@julsimon
YouTube: https://youtube.com/juliensimonfr
Podcast: http://julsimon.buzzsprout.com
Twitter https://twitter.com/@julsimon

Episode 14: AWS news Mar 20, 2020

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.

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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=oEcH8amMcT8
Amazon 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/julsimon
Medium blog: https://medium.com/@julsimon
YouTube: https://youtube.com/juliensimonfr
Podcast: http://julsimon.buzzsprout.com
Twitter https://twitter.com/@julsimon

Episode 13: Amazon Kendra special Mar 11, 2020

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.
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https://aws.amazon.com/kendra/

This podcast is also available in video at https://youtu.be/sd6Ydg0wAPs
For more content, follow me on:
* Medium https://medium.com/@julsimon
* Twitter https://twitter.com/@julsimon

Episode 12: AWS news and demos Mar 03, 2020

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.

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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/1704.04110
Train with Amazon SageMaker on your local machine: https://www.youtube.com/watch?v=K3ngZKF31mc
Amazon SageMaker Studio Deep Dive: https://www.youtube.com/watch?v=pGhn8Ax8QmQ

This podcast is also available in video at https://youtu.be/czngW9Wkjxw
For more content, follow me on:

Medium https://medium.com/@julsimon
Twitter https://twitter.com/@julsimon

Episode 11: XGBoost special Feb 24, 2020

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!
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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 10: AWS news and demos Feb 17, 2020

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.
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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.html
This 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 9 Feb 11, 2020

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.

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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 8 Feb 03, 2020

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.
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This podcast is also available in video at https://youtu.be/74LwQP9oKU4
For more content, follow me on:
- Medium: https://medium.com/@julsimon
- Twitter: https://twitter.com/julsimon

Episode 7 Jan 27, 2020

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.
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Francesco's Twitter: @Fra_Pochetti
Francesco's blog: https://francescopochetti.com/
This podcast is also available in video at https://youtu.be/DQh9FQxwvhI
For more content, follow me on:
* Medium: https://medium.com/@julsimon
* Twitter: https://twitter.com/julsimon

Episode 6 Jan 19, 2020

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.
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Cosmin's Twitter: https://twitter.com/cosminsanda
Cosmin'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/YqRd4Gh9a98
For more content, follow me on:
* Medium: https://medium.com/@julsimon
* Twitter: https://twitter.com/julsimon

Episode 5 Jan 13, 2020

In this episode, I talk about a couple of recent features, share some extra resources, and point you to pretty cool computer vision demo.
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News
* Amazon Comprehend - multi-label classification: https://aws.amazon.com/about-aws/whats-new/2020/01/amazon-comprehend-launches-multi-label-custom-classification/
* Amazon Translate - batch translation: https://aws.amazon.com/about-aws/whats-new/2020/01/amazon-translate-introduces-batch-translation/
Extra resources
* O’Reilly AI 2018 talk (SageMaker built-in algos): https://youtu.be/dGn1HAHbLWM
* O’Reilly AI 2019 talk (Introduction to NLP models): https://youtu.be/kwHGlTi27LY
* Sagify demo: https://youtu.be/cWv8zR2Qu94
Detectron2 demo
https://youtu.be/7R8-VAk0ruk
This podcast is also available in video at https://youtu.be/RE3gD1ti_0s
For more content, follow me on:
* Medium: https://medium.com/@julsimon
* Twitter: https://twitter.com/julsimon

Episode 4 Jan 05, 2020

In this episode, I have a chat with Pavlos Mitsoulis-Ntompos, a Data Scientist for the Expedia Group and an AWS Machine Learning Hero. We talk about real life ML, and what it takes for ML projects to be successful.
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Check out Sagify, an excellent CLI tool for Amazon SageMaker written by Pavlos:
* https://kenza-ai.github.io/sagify/
* End to end demo: https://youtu.be/cWv8zR2Qu94
This podcast is also available in video: https://www.youtube.com/playlist?list=PLJgojBtbsuc3HZ55IiEMD0gF1tPZo02nj

For more content, follow me at https://medium.com/@julsimon and at https://twitter.com/julsimon.

Episode 3: Machine Learning from A to Z Dec 30, 2019

In this episode, I explain in plain English 26 Machine Learning and Deep Learning terms that you need to know. If you're beginning with the field, this should save you quite a bit of frustration!
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Audio samples have been generated with Amazon Polly :)
The podcast is hosted at https://julsimon.buzzsprout.com, and is also available on YouTube at https://bit.ly/368Iz7g.

For more content, follow me at https://medium.com/@julsimon and at https://twitter.com/julsimon.

Episode 2: TensorFlow 2.0 special! Dec 25, 2019

In this episode, I focus on TensorFlow 2.0, the most popular open source library for Machine Learning. I explain in detail how it differs from TensorFlow 1.x, and how you can start using it on AWS: Deep Learning AMIs, Deep Learning Containers, and Amazon SageMaker.
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Additional resources:
* TensorFlow on AWS: https://aws.amazon.com/tensorflow
* My SageMaker notebook: https://gitlab.com/juliensimon/dlnotebooks/tree/master/keras/07-keras-fmnist-tf20
* A notebook giving you an overview of TensorFlow 2.0, by François Chollet, the creator of Keras: https://colab.research.google.com/drive/1UCJt8EYjlzCs1H1d1X0iDGYJsHKwu-NO

This podcast is also available in video: https://www.youtube.com/watch?v=Kqd7__Yllr0

For more content, follow me at https://medium.com/@julsimon and at https://twitter.com/julsimon.

Episode 1 Dec 23, 2019

In this episode, I talk about new features on Amazon Lex (chatbots), Amazon Textract (text extraction), Amazon Personalize (recommendation & personalization), and Amazon Transcribe (speech to text). I also demo profanity filtering with Transcribe (run for cover!).
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Additional resources mentioned in the podcast:
* Amazon SageMaker Ground Truth demo: https://www.youtube.com/watch?v=oEcH8amMcT8
* Amazon Textract demo: https://youtu.be/8kobcRynTTA
* Introduction to Graph Convolutional Networks: https://youtu.be/2bfxnj1J00A
This podcast is also available in video: https://www.youtube.com/watch?v=BretMPkpipg
For more content, follow me at https://medium.com/@julsimon and at https://twitter.com/@julsimon

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