ridhikag Goto Github PK

bigdata

This repository hosts the code/projects/demos/slides for Big Data technologies under Apache Hadoop and Apache Spark umbrella.

book-deep-learning-applications-with-applications-using-python

Chapterwise code available in the book

clustering-market-basket-analysis-and-recommendation-engine-in-r

Exploratory analysis of the customers & items in the dataset • Cluster the customers using Customer Segmentation • Analyze the items in the basket using Market Basket Analysis• Analyze the relationship between Customer and Items. • Use Association rules for MBA . 2. Use Arules and Apriori algorithm to suggest Recommendations. • Identify the percentage of items w.r.t all the orders from User. 3. Predict items in the customer’s cart using a logistic regression model . • Identify the correct predictors and interpret the model. • Evaluate the model’s predictive power on test data. • Match with the sample results given. Steps to do Download the data from Repository. Clean the data and run the R file

clustering-market-basket-analysis-recommendation-engine-in-r

Customer Insights : Customer Segmentation, Market Basket Analysis, Recommendation Engine

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

data-mining-python

Sheng's python codes for data manipulation and data mining

fashion-mnist

A MNIST-like fashion product database. Benchmark :point_right:

fbcunn

Facebook's extensions to torch/cunn.

free-machine-learning-books

A curated collection of free Machine Learning related eBooks

googlelanguager

R client for the Google Translation API, Google Cloud Natural Language API and Google Cloud Speech API

hinglish-sentiment

Sentiment analysis hinglish tweets

hinglishsentiment

linear-algebra-using-numpy

matrix, vector, mathematical operations using numpy

machine-learning-pca-and-bayesian-classification-on-radiology-x-ray-images

X-Ray Image processing and Classification in Python(From Scratch)

ml-coursera-python-assignments

Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.

natural-language-processing-on-facebook-comments

NLP, Text Mining on Social Media Data Facebook Graph API Noise removal, Lexicon Normalization(Stemming) Tokenization: Convert text into tokens. Unigram, bi-gram, Tri-grams Feature Engineering(Text to Features):Syntactical, Entity, Statistical Syntactical Parsing: Part of Speech Tagging Statistical Parsing: Document Matrix Entity Parsing :Topic Modelling Other Statistics:Frequency counts Sentiment Analysis:Positive/Negative Language Detection:Detect/Translate Network Analysis and Recommendation:Targeted Ads to Friends

recommendation-engine-in-r

Customer Insights

scala

Scala code files

sentiment-analysis-using-scala

Scrape real time data using Scala and sentiment analyis

social-media-workshop

Workshop: Analyzing and Collecting Social Media Data with R

spark-the-definitive-guide

Spark: The Definitive Guide's Code Repository

sql-questions-solved

SQL answers

thinkbayes

Code repository for Think Bayes.

thinkstats2

Text and supporting code for Think Stats, 2nd Edition