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#9 AI in India, US and Japan - with Gautam Bajaj

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When? This feed was archived on November 08, 2021 08:09 (2+ y ago). Last successful fetch was on November 06, 2020 03:37 (3+ y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 222665109 series 2422916
Content provided by dataspaning. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by dataspaning or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This episode features Gautam Bajaj, an engineer and data scientist that has worked with technologies mostly related to AI and machine learning. He has worked in India, USA, a leading video game company in Japan and is now consulting in Tokyo.

We talk about getting into the field of data science and AI and about the different working cultures in Japan, India, USA and Sweden. We get into the possibilities and challenges of AI and machine learning, such as scaling and keeping up with developments in such a rapidly evolving field.

Some things mentioned in this episode:- YanLeCun, AI course- Hadoop: a framework for distributed processing and big data- Kubernetes: a tool for running applications in "the cloud"- Medium, a blog platform- Recommender/recommendation system- Convolutional neural network (CNN)- Reinforcement learning- Generative adversarial networks (GANs)- Python- Amazon Web Services (AWS): cloud, web hosting etc.- Google Cloud Platform (GCP): cloud, web hosting etc.

We do not currently have any external partners and all opinions expressed are solely our own. Nothing discussed on this podcast should be considered as any kind of investment advice.

In this episode:- Gautam Bajaj, gautam1237 at gmail dot com- Martin Nordgren, works at Tobii, former engineer at Dirac, @martinjnordgren

Contact us:dataspaning.se@dataspaning @ Twitterdataspaning@gmail.com

  continue reading

35 episodes

Artwork
iconShare
 

Archived series ("Inactive feed" status)

When? This feed was archived on November 08, 2021 08:09 (2+ y ago). Last successful fetch was on November 06, 2020 03:37 (3+ y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 222665109 series 2422916
Content provided by dataspaning. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by dataspaning or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This episode features Gautam Bajaj, an engineer and data scientist that has worked with technologies mostly related to AI and machine learning. He has worked in India, USA, a leading video game company in Japan and is now consulting in Tokyo.

We talk about getting into the field of data science and AI and about the different working cultures in Japan, India, USA and Sweden. We get into the possibilities and challenges of AI and machine learning, such as scaling and keeping up with developments in such a rapidly evolving field.

Some things mentioned in this episode:- YanLeCun, AI course- Hadoop: a framework for distributed processing and big data- Kubernetes: a tool for running applications in "the cloud"- Medium, a blog platform- Recommender/recommendation system- Convolutional neural network (CNN)- Reinforcement learning- Generative adversarial networks (GANs)- Python- Amazon Web Services (AWS): cloud, web hosting etc.- Google Cloud Platform (GCP): cloud, web hosting etc.

We do not currently have any external partners and all opinions expressed are solely our own. Nothing discussed on this podcast should be considered as any kind of investment advice.

In this episode:- Gautam Bajaj, gautam1237 at gmail dot com- Martin Nordgren, works at Tobii, former engineer at Dirac, @martinjnordgren

Contact us:dataspaning.se@dataspaning @ Twitterdataspaning@gmail.com

  continue reading

35 episodes

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