ambareeshsrja16 Goto Github PK

.vim

Vim setup

ambareeshsrja16.github.io

Portfolio

bayesian_statistics_git

Temp

chalkpaint

A poor man's alternative to Varnish

datasets

A collection of datasets of ML problem solving

ddpg_torcs_pytorch

Using PyTorch and DDPG to play Torcs

deep_learning_backprop

Back Prop in Fully Connected Neural Network

dev_utils

Fork of JJ's dev_utils

docker-trino-fed

druid

Apache Druid: a high performance real-time analytics database.

ece143_project

Data Analysis and Visualization Project

emojify

Word vector based emojifier

functionapproximator

Function approximator to learn simple mathematical functions

image_classification_using_resnet__american-sign-language-dataset

Image Classification using ResNet - American Sign Language Dataset

image_segmentation_bdr

Projects using Bayesian Statistics for prediction

interesting-programming-challenges

Bunch of interesting programming challenges in Python

latest_resume

My latest resume

pandas_exercises

Practice your pandas skills!

profiles_rest_api

Source Code for Profiles REST API

prototype-selection-for-nearest-neighbor

A way to speed up nearest neighbor classification is to replace the training set by a carefully chosen subset of “prototypes”. A good strategy for choosing prototypes from the training set, bearing in mind that the ultimate goal is good classification performance, is implemented here

python-module-for-missing-data-imputation

Python Module for Missing Data Imputation

reinforcement-learning-with-tensorflow

Simple Reinforcement learning tutorials

reinforcementlearning

Reinforcement Learning Projects

scripts

Reusable scripts

simple_ml_projects

Simple Machine Learning Projects

style_transfer

Real-Time Style Transfer : Improvement on the Gatys approach, which produces high-quality images, but is slow since inference requires solving an optimization problem. Justin Johnson et al. came up with a variant of style transfer that was much faster and produced similar results to the original implementation. Their approach involves training a CNN in a supervised manner, using perceptual loss function to measure the difference between output and ground-truth images.

surgical_tool_tracking

Python scripts for Surgical Tool Tracking using Deep Learning for feature point extraction

utility_functions_python

Set of utility functions in Python for different purposes

vision_opencv