Name: Niranjan Anandkumar
Type: User
Company: Deceptive AI
Bio: Founder & CTO@Deceptive AI
Making AI Accessible
Full Stack Deep Learning , CV, NLP and MLOps |
Solution Architect |
Twitter: NiranjanHBP
Location: Bengaluru, India
Blog: https://www.linkedin.com/in/niranjanaryan/
Niranjan Anandkumar's Projects
Models and examples built with TensorFlow
Maintain your CV in Markdown :sparkles:
TensorFlow Neural Machine Translation Tutorial
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Obstacle Tower Environment
Machine Learning for OpenCV: A practical introduction to the world of machine learning using OpenCV and Python
Toolkit for efficient experimentation with various sequence-to-sequence models
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
Windows and Linux version of Darknet Yolo v3 & v2 Neural Networks for object detection
Teaching material for python json workshop
The "Python Machine Learning (1st edition)" book code repository and info resource
The "Python Machine Learning (2nd edition)" book code repository and info resource
Data Modelling, Analysis and Optimization
Python Data Science Handbook: full text in Jupyter Notebooks
Tensors and Dynamic neural networks in Python with strong GPU acceleration
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
Question answering dataset featured in "Teaching Machines to Read and Comprehend
A React component to make correcting automated transcriptions of audio and video easier and faster. By BBC News Labs. - Work in progress
Python Implementation of Reinforcement Learning: An Introduction
Implementation of Research paper to production code
Create your Professional/Educational resume using LaTeX
rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.
Implement SC-LSTM model for text generation in control of words, in Python/TensorFlow
a scaleable and efficient crawelr with docker cluster , crawl million pages in 2 hours with a single machine
scikit-learn: machine learning in Python
A general-purpose encoder-decoder framework for Tensorflow