radrangi Goto Github PK

a-2017

Public Repository for cs109a, 2017 edition

agile_data_code_2

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

ai-notebooks

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker

analytics-integration-samples

Repository contains samples to integrate Watson IoT with different analytics services

anomaly-detection

Anomaly Detection model uses Spark for training and Spark Streaming for testing

anomaly_detection

ataribreakout

awesome-apache-airflow

Curated list of resources about Apache Airflow

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-machine-learning

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

awesome-mlops

A curated list of references for MLOps

awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

awesome-scala

A community driven list of useful Scala libraries, frameworks and software.

azure

best-heart-drug-selection

Created for toolchain: https://console.bluemix.net/devops/toolchains/74c65cd6-d1b4-444e-92e9-0b065ccbe1d8?env_id=ibm%3Ayp%3Aus-south

cellular_automata

we have a matrix with N columns and M rows. Each entry in the matrix is either 0 or 1. We always initialize Row 1. Given a rule , we construct the subsequent row by applying the rule to the previous row and so on. We can extend the number of rows indefinitely. Guided by one of the rules of cellular automata described : http://www.wolframscience.com/nksonline/page-53 Also added the feature to locate all occurances of a specific pattern. The pattern is based on 6 matrix elements located in two subsequent rows. This kind of analysis finds application in pattern recognition (growth of crystals in snowflakes, development of patterns in sea shells, improving unclear images, tracing mutaion)

cheat-sheets

cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers

cloudml-dist-mnist-example

cloudml-samples

Samples for Google Cloud Machine Learning Engine

confluent-kafka-python

Confluent's Apache Kafka Python client

cookbook

The Data Engineering Cookbook

cs-229

Assignment Solutions to Coursera CS-229 Machine Learning by Stanford

cs-video-courses

List of Computer Science courses with video lectures.

cs229-project

Class project for CS 229, Machine Learning at Stanford, 2013

ctimages

CT images analysis and prediction. Project in Pattern Recognition course

data-analysis-and-machine-learning-projects

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

data-analysis-and-visualisations

Python script for Data Analysis and Visualisations