radrangi Goto Github PK

data-science--cheat-sheet

Cheat Sheets

data-science-cookbook

:mortar_board: Jupyter notebooks from UFC data science course

data-science-on-gcp

Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017

data-science-your-way

Ways of doing Data Science Engineering and Machine Learning in R and Python

dataflow-opinion-analysis

Opinion Analysis of News, Threaded Conversations, and User Generated Content

datalab-samples

dataquest_eng

Here's how to get DataQuest's Data Engineering Track missions' content to work on your localhost. Using data from my Valenbisi ARIMA modeling project, I document my steps using PostgreSQL, Postico, and the Command Line to get our DataQuest exercises running out of a Jupyter Notebook.

datasciencepython

common data analysis and machine learning tasks using python

dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deep-q-atari

Keras and OpenAI Gym implementation of the Deep Q-learning algorithm to play Atari games.

deep-q-network-breakout

This is an implementation of Deep Q Learning (DQN) playing Breakout from OpenAI's gym with Keras.

deep-reinforcement-learning-for-atari-games

Train our agent to play Breakout Game using 4 models and 2 CNN structures

deeplearningtutorials

Deep Learning Tutorial notes and code. See the wiki for more info.

deeplearntoolbox

Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

devopsinsights-toolchain-20181110153202637

Created for toolchain: https://console.bluemix.net/devops/toolchains/846962e0-7a7b-4170-b6e1-a716e869ef23?env_id=ibm%3Ayp%3Aus-south

dl_modis

Test based on the code of: Rußwurm M., Körner M. (2017). Temporal Vegetation Modelling using Long Short-Term Memory Networks for Crop Identification from Medium-Resolution Multi-Spectral Satellite Images. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017.

dltfpt

Deep Learning with TensorFlow, Keras, and PyTorch

docs

Documentation for Grin and Mimblewimble

domain-transfer-network

TensorFlow Implementation of "Unsupervised Cross-Domain Image Generation"

driverlessai-recipes

Recipes for Driverless AI

ebimage

:art: Image processing toolbox for R

example-project

Example Python DS project

examples

Demo applications and code examples for Confluent Platform and Apache Kafka

examples-1

Apache Kafka and Confluent Platform examples and demos

face-recognition

FACE RECOGNITION ---------------- The Yale Face Database contains 165 grayscale images in GIF format of 15 individuals. There are 11 images per subject, one per different facial expression or configuration: center-light, w/glasses, happy, left-light, w/no glasses, normal, right-light, sad, sleepy, surprised, and wink. Your tasks are the following: 1. I have divided image into small blocks and extracted local binary patterns (LBP) from each block. Concatenated all LBP histograms to make a feature vector of an image. 2. Another feature vector is created out of gray levels of integral image. 3. Finally gray levels of image have been used as the last feature vector. 4. After Concatenating all feature vectors. I have Taken four images of each person for testing and the rest as training examples. 5. Using PCA to classify image for one-verses all classification scheme, i have shown results for few images that are selected randomly and reported the accuracy for all testing images using individual feature sets (gray level, integral, and LBP separately) and also for concatenated feature sets.

fast-data-dev

Kafka Docker for development. Kafka, Zookeeper, Schema Registry, Kafka-Connect, Landoop Tools, 20+ connectors

free-programming-books

:books: Freely available programming books

freqtrade

Free, open source crypto trading bot