Expressing ideas in an easily understandable format is considered an art in education, and crucial if you want users, readers or community members to be engaged.

Over the years, I've made a constant effort to share my learnings and findings on a very high level, making it understandable and comprehensible for beginners, intermediate and advanced users.

I write light, engaging but technically complex content for diverse audiences. My areas of expertise include education, machine learning, product engineering and data science.


I have collaborated on educational content with some of the biggest technical publications in the world.

Technical Writing

"Deep convolutional generative adversarial networks with TensorFlow", O'Reilly Media & Google.

"PyTorch vs. TensorFlow", Towards Data Science.

"Reinforcement Learning: The quirks", Towards Data Science.

"How OpenMined will revolutionize data privacy, protection and collection", Becoming Human & OpenMined.

"Turning Feedback Data into Actionable Advice", HackerNoon.

"What are Variational Autoencoders? A simple explanation", Self-Published.

"Denoising Autoencoders explained", Towards Data Science.

Technical Literature Review

I have repeatedly been working with O'Reilly Media to provide detailed feedback to authors prior to release of their technical books.

"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition" by Aurélien Geron.

"Deep Learning from Scratch" by Seth Weidman.

"Strengthening Deep Neural Networks" by Katy Warr.

"Programming PyTorch for Deep Learning" by Ian Pointer.

"Practical Artificial Intelligence with Swift" by Tim Nugent, Paris Buttfield-Addison, Jonathon Manning, Mars Geldard.