pursh2002

Big-Data-Analytics-in-Healthcare-Notes

Modeling and Analysis,Data and Computing,Health Business Context and Problem Solving by gaining hands-on experience with scalable machine learning algorithms, big data systems and healthcare data analytic applications

corpnce

Corpnce is India's First Gold Standard Project Based Learning (PBL) Institute offering Deep Learning (AI), Data Science, Big Data, Phython etc. courses.

100-Days-Of-ML-Code

100 Days of ML Coding

100DaysofMLCode

Adversarial_Autoencoder

A wizard's guide to Adversarial Autoencoders

Algorithms..

Analytics-in-python

Blockchain

study material/practice

breast_cancer_classification

This artificial neural network predicts whether a tumour is benign or malignant.

COPA

Code accompanying our CIKM paper: "copa: constrained parafac2 for sparse & large datasets"

Coursera

Quiz & Assignment of Coursera

developer-roadmap

Roadmap to becoming a web developer in 2018

Digit-Recognizer

Machine Learning classifier for recognizing the digits.

fhir

FHIR Protocol Buffers

Guide-to-SQL-exercise

Data Exploration,cleaning,modelling

IOT

Studymat

Machine-Learning

Study Group Research and Learning for Artificial Intelligence: Coursera Learning: Created by: Stanford University/Andrew Ng

Machine-Learning-Tools

machine learning with python

ml-cheatsheet

Machine learning cheatsheet

playground-2U5mn206

Tech.io playground

playground-UVeDOgW0

Tech.io playground

pwm-rc-raspberry-pi-arduino

arduino and raspberry pi controlled rc car/ truck PWM with wireless controller

python_notes

Quantum-

reference

Reference implementations of MLPerf benchmarks

Sunday-StudyGroup-Mastering-Artificial-Intelligence

t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

the-elements-of-reinforcement-learning

Reinforcement Learning (RL) is believe to be a more general approach towards Artificial Intelligence (AI). RL is the foundation for many recent AI applications, e.g., Automated Driving, Automated Trading, Robotics, Gaming, Dynamic Decision, etc. With concrete examples, this repository tries introduce clearly the basic elements of Reinforcement Learning, e.g., Agent, Environment, State, State Transition, Policy, Action, Reward, Future Return, Discounted Future Return, Exploration & Exploitation, Markov Decision Processing, The Bellman Equation, Policy-based Learning, Value-based Learning, etc.

Visualization

study material/practice

work_on_new_python_stuff