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

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

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

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:
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* Twitter: https://twitter.com/julsimon

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.

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.

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.