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100-days-of-ml-code

A day to day plan for this challenge. Covers both theoritical and practical aspects

2017-ecml-forensic-unsupervised

60days-of-udacity

Repo including all the daily updates of #60daysofudacity Udacity Challenge

ai_dhino

This is an AI that plays the Dhino game availble on the google Chrome. I developed it using Opencv. It grabs the screen and detects the upcoming barriers and overcomes the barriers.

async-rl

Tensorflow + Keras + OpenAI Gym implementation of 1-step Q Learning from "Asynchronous Methods for Deep Reinforcement Learning"

async-rl-1

Implementation of Asynchronous Methods for Deep Reinforcement Learning in TensorFlow + OpenAI Gym

asynchronous_rl

aura

GDG Chapter website template

automated-bug-triaging-to-developer

For popular software systems, the number of daily submitted bug reports is high. Triaging these incoming bugs is a time consuming task. Major part of bug triaging is the assignment of a bug report to a developer with the appropriate expertise, who can resolve/fix the bug without reassigning to some other developer. We present an approach to automatically suggest developers who have the appropriate expertise for handling a bug report based on the identified software component the bug may reside in, obtained from the short description of the bug report. Our work is first to examine the impact of multiple machine learning dimensions( classifiers and training history) along with the ranked list of developers for prediction accuracy in bug assignment. We validate our approach on Eclipse Bugzilla covering 2,868,000 bug reports consisting of 253 components. We demonstrate that our techniques can achieve up to 93% prediction accuracy in bug assignment and significantly reduce the aberrant assignment of bugs. We compared the prediction time for our dataset using various algorithms such as Naive Bayes Text Classifier, Multinomial Naive Bayes and Linear SVM. We arrived at a conclusion that SVM provides higher prediction time and less learning time.

awesome-deeplearning-resources

Deep Learning and deep reinforcement learning research papers and some codes

awesome-federated-computing

:books: :eyeglasses: A collection of research papers, codes, tutorials and blogs on Federated Computing/Learning.

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-machine-learning-on-source-code

Cool links & research papers related to Machine Learning applied to source code (MLonCode)

azure_machine_learning

This is the code for "Azure Machine Learning" By Siraj Raval on Youtube

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

basic_model_scratch

Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library

big-data-machine-learning

book-socialmediaminingpython

Companion code for the book "Mastering Social Media Mining with Python"

botbuilder-tools

Tools for developers building bots with Microsoft Bot Framework

capstone_project

Predicting Global Supply Chain Outcomes for Essential HIV Medicines using Machine Learning Techniques. Capstone original project for Udacity Machine Learning Engineer Nanodegree.

chatbot-ai

Chatbot AI for Machine Learning for Hackers #6

chatbot-retrieval

Dual LSTM Encoder for Dialog Response Generation

chatterbot

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

content-aws-csa2019

Adrian's AWS CSA Assoc Course Refresh 2019

covid-19-scanner

covid-net

COVID-Net Open Source Initiative

covid19

cs291k

🎭 Sentiment Analysis of Twitter data using combined CNN and LSTM Neural Network models

daily-coding-problem

Solutions to problems sent by dailycodingproblem.com

daily-coding-python