Chandra P.

Chandra P.

BengaluruIndia
Job Success
Top Rated

Software Architect, Deep Learning and Software Engineer

Specialties and Interest areas: Deep Learning, Pattern Recognition, Image Processing & NeuroScience. Scalable System Design and Solution Architecting.
Jul 6, 2021 - Jul 29, 2022

No feedback given

Private earnings
Rating is 3.6 out of 5.
3.60 Jun 20, 2021 - Jul 11, 2021
Private earnings
Rating is 5 out of 5.
5.00 Aug 25, 2017 - Aug 23, 2020

"Chandra is very knowledgable and was indispensible for our project. Would definitely hire again."

Private earnings
Jul 25, 2017 - Sep 5, 2017

No feedback given

Private earnings

Chandra P. has more jobs. Create an account to review them

Portfolio

Augment a dataset of about 30,000 to nearly 3,00,000 using multiple Image Processing techniques like rotation, scaling, affine transformation, random noise introduction, translation etc
Data Augmentation
The goal of the project was to classify around 28000 images into 150 classes. I was asked to fine tune an existing model to fit the data provided by the client. I worked on Keras + Tensorflow project to train the model and fit the client dataset. I was able to make the model's accuracy by over 85%.
Image Classification -- Fine Tuning
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Chandra P.

Chandra P.

BengaluruIndia
Job Success
Top Rated
7
Total Jobs
2,674
Total Hours

Software Architect, Deep Learning and Software Engineer

Specializes in
Specialties and Interest areas: Deep Learning, Pattern Recognition, Image Processing & NeuroScience. Scalable System Design and Solution Architecting.
Jul 6, 2021 - Jul 29, 2022

No feedback given

Private earnings
Rating is 3.6 out of 5.
3.60 Jun 20, 2021 - Jul 11, 2021
Private earnings
Rating is 5 out of 5.
5.00 Aug 25, 2017 - Aug 23, 2020

"Chandra is very knowledgable and was indispensible for our project. Would definitely hire again."

Private earnings
Jul 25, 2017 - Sep 5, 2017

No feedback given

Private earnings

Chandra P. has more jobs. Create an account to review them

Portfolio

Augment a dataset of about 30,000 to nearly 3,00,000 using multiple Image Processing techniques like rotation, scaling, affine transformation, random noise introduction, translation etc
Data Augmentation
The goal of the project was to classify around 28000 images into 150 classes. I was asked to fine tune an existing model to fit the data provided by the client. I worked on Keras + Tensorflow project to train the model and fit the client dataset. I was able to make the model's accuracy by over 85%.
Image Classification -- Fine Tuning
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