Santapaji
I am an aspiring data science enthusiast who enjoys connecting the dots: be it ideas from different disciplines, or people from different teams.
University of Texas ArlingtonTexas
Pinned Repositories
APPLE_PROJ_COGNIZANT
App usage of well established Apple products 100 customers who are using the apple device they want to use the apple media products as well as apple news app Find out the number of users enrolled in Apple devices (iPhone,iPad, macbook apple desktop etc) and uses Apple apps (internal and external) Get 8 files - 5 external and 3 internal files 5 external files - 2 are csv, 2 json, 1 spreadsheet we have to bring into unix as raw data and while move this to mysql we have all the data quality rules 5 data quality rules need to apply while bringing data from external files to unix system make we us all the data quality rules(NULL-surname, space can be used ) and From the 2 csv files - music data from Sony and Tseries (vendors from sony and T Series) Json files - videos data from US and China (video streaming data/audio streaming data) Find the video app it can be another country also Spreadsheet - News data (anonymous)-news data (Times of India) need to work on it In the 4 tables - 2 tables have existing users using music and video products 1 table already has news data 1 master table should have all the products containing existing and new users every table should have at least 10 columns all the files to be loaded into UNIX (join all the files with tables) 10 transformation rules to be coded in Python and loaded into master table Create one more table which should have combination of all the segments for individual customers (at least 100 customers - each should be associated with one segment ID, each video/audio should have own unique segment ID) Create 3 age groups - under 18, under 13, under 21 (for India) under 18, under 13, above 18 - for US All the customers that are above 18 should have access to all the products with segment ID and product combination All the cutomers under the age between 13 and 18 have the access to audio All the customers that are under 13 should have access to only music with segment ID and product combination After uploading everything show charts of all age group based on age and products Technology - unix, python, sql, data visualisation, hive, hdfs Product has to be well developed and tested Unix Shubham,Sanjay Python Balasubramani, Joswin, Abhisangh MySQL Joswin,Priyanaka,Saurab, Somesh,Shubham Data Visualization Joswin,Somesh,Yash,Abhisangh Hive Saurabh Hadoop Sanjay, Saurabh.
ARORA
THIS CONTAINS MY 2 TASKS FOR CNN AND CONTRASTIVE LEARNING
COVID19ANALYSIS
covid 19 analysis and prediction using R
Data-Mining
data_Mining_project
This is my Data mining project which aims to build a image classifier and compare the results among various classifiers taught in class such as CNN, KNN, NBC, SVM and XGboost
DROPDOWN-LIST_WT
EVENT-REGISTERATION-WEBSITE
WT ASSIGNMENT 2
Facial-Emotion-Expressions
post describes the process of building an image classifier using a dataset of facial expressions. The author uses the Keras deep learning library and provides a detailed walkthrough of the steps involved in the process. The steps include data preprocessing, building and training the model, and evaluating the model's performance.
map-website
A tool to recursively scrape websites.
Music-player
Santapaji's Repositories
Santapaji/APPLE_PROJ_COGNIZANT
App usage of well established Apple products 100 customers who are using the apple device they want to use the apple media products as well as apple news app Find out the number of users enrolled in Apple devices (iPhone,iPad, macbook apple desktop etc) and uses Apple apps (internal and external) Get 8 files - 5 external and 3 internal files 5 external files - 2 are csv, 2 json, 1 spreadsheet we have to bring into unix as raw data and while move this to mysql we have all the data quality rules 5 data quality rules need to apply while bringing data from external files to unix system make we us all the data quality rules(NULL-surname, space can be used ) and From the 2 csv files - music data from Sony and Tseries (vendors from sony and T Series) Json files - videos data from US and China (video streaming data/audio streaming data) Find the video app it can be another country also Spreadsheet - News data (anonymous)-news data (Times of India) need to work on it In the 4 tables - 2 tables have existing users using music and video products 1 table already has news data 1 master table should have all the products containing existing and new users every table should have at least 10 columns all the files to be loaded into UNIX (join all the files with tables) 10 transformation rules to be coded in Python and loaded into master table Create one more table which should have combination of all the segments for individual customers (at least 100 customers - each should be associated with one segment ID, each video/audio should have own unique segment ID) Create 3 age groups - under 18, under 13, under 21 (for India) under 18, under 13, above 18 - for US All the customers that are above 18 should have access to all the products with segment ID and product combination All the cutomers under the age between 13 and 18 have the access to audio All the customers that are under 13 should have access to only music with segment ID and product combination After uploading everything show charts of all age group based on age and products Technology - unix, python, sql, data visualisation, hive, hdfs Product has to be well developed and tested Unix Shubham,Sanjay Python Balasubramani, Joswin, Abhisangh MySQL Joswin,Priyanaka,Saurab, Somesh,Shubham Data Visualization Joswin,Somesh,Yash,Abhisangh Hive Saurabh Hadoop Sanjay, Saurabh.
Santapaji/ARORA
THIS CONTAINS MY 2 TASKS FOR CNN AND CONTRASTIVE LEARNING
Santapaji/COVID19ANALYSIS
covid 19 analysis and prediction using R
Santapaji/Data-Mining
Santapaji/data_Mining_project
This is my Data mining project which aims to build a image classifier and compare the results among various classifiers taught in class such as CNN, KNN, NBC, SVM and XGboost
Santapaji/DROPDOWN-LIST_WT
Santapaji/EVENT-REGISTERATION-WEBSITE
WT ASSIGNMENT 2
Santapaji/Facial-Emotion-Expressions
post describes the process of building an image classifier using a dataset of facial expressions. The author uses the Keras deep learning library and provides a detailed walkthrough of the steps involved in the process. The steps include data preprocessing, building and training the model, and evaluating the model's performance.
Santapaji/map-website
A tool to recursively scrape websites.
Santapaji/Music-player
Santapaji/NBC_for_rotten_tomatoes
Santapaji/static_website
Santapaji/WT_ASS_04