Abhinav Prakash
Senior Software Engineer at Pocket FM
Bengaluru, Karnataka, India
Summary
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Senior🎓
Top SchoolAbhinav Prakash is a Senior Software Engineer with 7 years of experience building scalable backend systems and production ML tooling, currently working at Pocket FM in Bengaluru. He has hands-on expertise integrating payment systems, building resilient file and export microservices, and shipping multilingual e-commerce features from his time at Dukaan. An active open-source contributor to major TensorFlow projects (including d2l-en and tensorflow/datasets), he has applied deep learning knowledge to optimization algorithms, RNNs, dataset refactors and model interpretability notebooks used widely in research and teaching. Founder of xiken.tech and former Google DSC lead, he pairs product-minded entrepreneurship with community leadership (co-organiser of PyData Bhubaneswar). He also won a Best Paper award for applied research, reflecting a blend of practical engineering and academic rigor.
7 years of coding experience
4 years of employment as a software developer
Bachelor of Technology - BTech, Computer Science, Bachelor of Technology - BTech, Computer Science at Gandhi Institute for Technological Advancement
Github Skills (25)
interpretation10
python10
data-set10
machine-learning10
data-model10
datasets10
google-colab10
deeplearning-ai10
deep-learning10
tensorflow10
user-data10
google-colaboratory10
jupyter-notebook10
documentation10
visualization9
Programming languages (12)
Github contributions (5)
tensorflow/examples
Dec 2019 - Aug 2020
TensorFlow examples
Role in this project:
Technical Writer
Technical WriterContributions:41 commits, 32 PRs, 26 comments in 7 months
Contributions summary:Abhinav primarily focused on updating and correcting documentation within the TensorFlow examples repository. Their contributions involved fixing typos, correcting grammatical errors, and updating notebooks. The user also made minor corrections to colab buttons and source code comments.
tensorflow
d2l-ai/d2l-en
Jun 2020 - Nov 2020
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Role in this project:ML Engineer
ML EngineerContributions:1 review, 26 commits, 23 PRs in 5 months
Contributions summary:Abhinav primarily contributed to the TensorFlow-related components of the deep learning book. They modified code related to optimization algorithms, including minibatch-SGD and gradient descent, and also updated code related to recurrent neural networks (RNNs). Their contributions involved changes to core TensorFlow files, suggesting a focus on implementing or refining deep learning concepts within the book's content. This demonstrates a strong understanding of TensorFlow and its application in deep learning.
kagglepythontensorflowgaussian-processesnatural-language-processing
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