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Essential Techniques for Deep Learning to avoid Overfitting #4
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Hi @sumankanukollu |
Hi Ani,
Sorry I won't be available during that time.
I will be in Hyderabad, to meet our executives.
Regards,
Suman Kanukollu
Mobile No.: +91 9703049427
https://www.linkedin.com/in/suman-kanukollu
…On Mon, May 8, 2023 at 5:48 PM Ani ***@***.***> wrote:
Hi @sumankanukollu <https://github.com/sumankanukollu>
Are you based out of Bangalore or do you need to travel?
If you can travel, would you be available to present this month 20th
morning?
We're also designing a poster this time as an experiment. Would you be
open to sharing your pic to be put up on the poster?
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Hi @sumankanukollu |
Hi,
Thanks for your mail.
I recently relocated to Hyderabad.
So I can present this virtually, if possible.
Regards,
Suman Kanukollu
Mobile No.: +91 9703049427
https://www.linkedin.com/in/suman-kanukollu
…On Tue, Jul 4, 2023 at 2:00 PM Ani ***@***.***> wrote:
Hi @sumankanukollu <https://github.com/sumankanukollu>
Are you willing to present this in July meetup?
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This one's a physical meetup unfortunately. If we do virtual event, will reach out. Thanks. |
No worries, thanks for the heads up!
Regards,
Suman Kanukollu
Mobile No.: +91 9703049427
https://www.linkedin.com/in/suman-kanukollu
…On Wed, Jul 5, 2023 at 4:04 PM Ani ***@***.***> wrote:
This one's a physical meetup unfortunately. If we do virtual event, will
reach out. Thanks.
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Title of the talk
Essential Techniques for Deep Learning to avoid Overfitting
Description
In deep learning, overfitting is a common problem that can hinder the performance and generalisation of models. To address this issue, deep learning practitioners use a variety of techniques to regularize their models, including dropout, data augmentation, early stopping, L1 and L2 regularization, and batch normalization.
In this talk, we will explore the essential techniques for avoiding overfitting in deep learning, and discuss their benefits and limitations.
By the end of this session, participants will have a solid understanding of the essential techniques for avoiding overfitting in deep learning, and will be able to apply these techniques to their own projects and research.
What format do you have in mind for your talk?
Talk
Table of contents
Some potential questions to explore during the session include:
What domain would you say your talk falls under?
Data Science & Machine Learning
Duration in minutes (including Q&A)
60
Prerequisites
Speaker bio
https://www.linkedin.com/in/suman-kanukollu/
The talk/workshop speaker agrees to
Share the slides, code snippets and other material used during the talk
If the talk is recorded, you grant the permission to release
the video on BangPyper's YouTube
channel
under CC-BY-4.0
license
Not do any hiring pitches during the talk and follow the Code
of
Conduct
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