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20newsgroups-data-mining

Using LIME and Spark MLlib, validate sentiment analysis using two classes - Atheism and Christianity with spark data pipeline and calculating F1-score, accuracy and class probabilities

aiddata

AidData's Core Research Release 3.1 is a corrected snapshot of AidData's entire project-level database from April 2016. This database includes commitment information for over 1.5 million development finance activities funded between 1947 and 2013, covers 96 donors, and includes ODA, OOF flows, Equity Investments, and Export Credits where available.

building-scalable-apps-with-redis-and-node.js

This is the public repo for the book, Building Scalable Apps with Redis and Node.js. Published by Packt Publishing. You can purchase the book at: https://www.packtpub.com/web-development/building-scalable-apps-redis-and-nodejs

chatbot

Embedding chatbot in web-app

consumer_complaints

crypto

this is our repo for crypto project 2

d3-maps

Amount donated vs Received by countries

data-science-portfolio

data-science-projects

Applying machine learning algorithms on various datasets

deeplearning.ai

Deeplearning.ai

denoise-noisy-docs

Removal of stains from noisy docs using image processing, machine learning, neural nets and autoencoder

denoising-dirty-documents-using-r

Removal of stains from documents by providing dirty and clean images as data-sets for the model to learn and the model would clean the test images by observing results from the training dataset using Linear Regression.

devops-techtalk

AWS LearnUp : DevOps on AWS

fashion-mnist

Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. Zalando intends Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.

formula1

Formula1 Grand Prix data analysis with interactive dashboards for the historic data from 1950-2017

foursquare-clone

Oingo is a new mobile app named that allows users to share useful information via their mobile devices based on social, geographic, temporal, and keyword constraints. The main idea in oingo is that users can publish information in the form of short notes, and then link these notes to certain locations and certain times. Other users can then receive these notes based on their own location, the current time, and based on what type of messages they want to receive

gandalf1819.github.io

Personal website

golabs

Lab skeletons

google-interview-university

A complete daily plan for studying to become a Google software engineer.

gym

A toolkit for developing and comparing reinforcement learning algorithms.

histogram-equalizer

Histogram equalization is a technique for adjusting image intensities to enhance contrast

image-denoising

Image denoising techniques in Computer Vision using Box, Gaussian and Median filter

introml

Python tutorials for introduction to machine learning

kubernetes

Production-Grade Container Scheduling and Management

lime

Lime: Explaining the predictions of any machine learning classifier

machine-learning-with-tensorflow

Implementing Machine Learning algorithms using Tensorflow

machine_learning_examples

A collection of machine learning examples and tutorials.

nevala

Simple notepad using WPF

nevala-v_2.0

IPython docked

nyc-parking-violations

Using MapReduce and Spark to explore NYC Parking Violations