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Name: Anurag Patil
Type: User
Location: Dallas/Fort Worth
Name: Anurag Patil
Type: User
Location: Dallas/Fort Worth
Code for my videos on big data analytics with Apache Spark using Scala.
Big Data (HDFS MapReduce: “1. Inverted Index forming relationship between words and the file names in which they appear 2. Forming a relationship between author and words used by those authors in the different books/papers published by them”.
Pokémon Go! became a very famous augmented reality (AR) game in 2016 summer. 1. In this project, we want to understand the success of the mobile app game. The goal of the project is to predict values of "Total IOS Ratings" and "Total Android Ratings" for 2016/11/01 11:50 PM. 2. For that we did web scraping using BeautifulSoup4, Constructed a Pandas data frame, explored/ and visualized the numeric data using matplotlib or seaborne by generating scatter matrix and calculating the Pearson’s correlation coefficients for the identified pairs. 3. Analyzed the app’s screenshot images using deep learning with TensorFlow 4. Finally to used sklearn to build machine learning models to predict the app’s review counts using cross validation algorithms like Linear Regression, Ridge Regression and Lasso. TechStack: ( Python - 3.6 Pycharm(Community Edition) - 3.5.1 Anaconda 3 - 4.3.1 BeautifulSoup, TensorFlow )
Reformatted and created new repositiries for projects which were created in this repository
Apache Spark
Big Data (Spark RDD / SQL POC): “1. Inverted Index forming relationship between words and the file names in which they appear 2. Forming a relationship between author and words used by those authors in the different books/papers published by them”. With the help of Spark (RDD and SQL).
This repo is for demonstration purposes only.
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