Ashutosh Upadhye's repositories
Machine-Learning-Naive-Bayesian-Classifer
Naive Bayes classifiers are highly scalable, requiring a number of parameters linear in the number of variables (features/predictors) in a learning problem. Maximum-likelihood training can be done by evaluating a closed-form expression,[1]:718 which takes linear time, rather than by expensive iterative approximation as used for many other types of classifiers.
Algorithms_LeetCode
Solved Algorithms for the leetcode explore section
AndroidWDLJ
Testing different convolutional neural networks with latest android SDK.
cosmo-demos
SPICE-Enhanced Cosmographia Tutorials
JavaMultiThreading
Implementation of locks, semaphores and threadpools along with threading basics
Neural_Network_Implementations
Implementations of Neural Networks from scratch using PyTorch or TensorFlow
reverse-interview
Questions to ask the company during your interview