Gopala KR

summary. summaries of all the papers I read

meta-learning. meta-learning research

ai-learning-roadmap. List of all AI related learning materials and practical tools to get started with AI apps

a-week-in-wild-ai. 360 view on ai/ml/dl applications

ai-applications. roadmap to applied ai

DRL-Agents. research and implementations of Deep RL agents and their applications

pbl. Curated list of project-based tutorials

10-weeks. 10-weeks of technology exploration

DL-on-Silicon. research, experimentation and implementation of hardware-agnostic accelerated DL framework

generative-models. research and implementations of Generative Models(GANs, VAEs and Autoregressive models) and their applications

ConvNets. research and implementations of CNNs and their applications

notebooks. A collection of practical handson jupyter notebooks on bigdata/ml/dl/rl/cv/nlp/ds/scipy/viz-lib/various command lines

language-models. research and implementations of recurrent neural networks and their applications

kaggle-solutions. https://www.kaggle.com/gopalakr

code-rush-101. Jupyter Notebook

Quantum-Dots.

autoencoders. implementations of various types of auto-encoders in tensorflow(in progress)

trending-repos. trending repositories and news related to AI

fundamentals. fundamentals of ci

SoTA. benchmarking state-of-the-art results for ml/dl problems

system-design-primer. large scale system designs