Anmol Krishan Sachdeva
- Currently, working as a Platform Software Engineer at Bigbasket, India (India's largest online food and grocery store).
- MSc in Advanced Computing (Machine Learning, Artifical Intelligence, Robotics, Cloud Computing, and Computational Neuroscience), University of Bristol, United Kingdom.
- International Tech Speaker (spoke at numerous National and International Conferences).
- Last year, gave a talk about "Recurrent Neural Networks and Long Short-Term Memory Networks (LSTMs)" at EuroPython, Edinburgh, Scotland - July 2018.
Link: Recurrent Neural Networks and Long Short-Term Memory Networks
- Last year, gave a talk about "Understanding and Implementing Recurrent Neural Networks using Python" at GeoPython, Basel, Switzerland - May 18.
Link: Understanding and Implementing Recurrent Neural Networks using Python
- Have 8+ International Publications. [Latest work got published in ACM CHI 2018. The project was exhibited in Montreal, Canada.]
- Received 6 Honours and Awards (International and National level).
- Represented India at International Hackathons like Hack Junction’16, Finland and Hack the North’16, Canada. Got invited for more than a ‘dozen’ of prestigious International Hackathons (PennApps’17, HackNY’17, Hack Princeton’17 and many more) and Conferences.
- A Microsoft Certified Professional, Microsoft Technology Associate, IBM Certified Web Developer, and Hewlett Packard Certified Developer.
- Former Software Developer Intern at IBM & an ALL STACK DEVELOPER capable of designing and developing solutions for Mobile, Web, Embedded Systems, and Desktop. Areas of interest are Computational Neuroscience, Deep Learning, and Cloud Computing.
Understanding and Implementing Generative Adversarial Networks (GANs): One of the BIGGEST Breakthroughs in the Deep Learning Revolution
With the computational resources becoming more powerful over time, tremendous advancements are being made in the field of Deep Learning. Generative Adversarial Networks (GANs) are one amongst such advancements. Interested in knowing how to "generate" content (images, music, speech, prose, and much more) instead of "classifying" one into categories? Let's dive into the granularities of Generative Adversarial Networks (GANs): One of the BIGGEST Breakthroughs in the Deep Learning Revolution.