Paras Yadav (@ParasYadav94)
  • Stars
    star
    16
  • Global Rank 731,699 (Top 26 %)
  • Followers 5
  • Following 1
  • Registered almost 6 years ago
  • Most used languages
    Python
    57.1 %
    R
    28.6 %
    SAS
    14.3 %
  • Location 🇮🇳 India
  • Country Total Rank 30,281
  • Country Ranking
    SAS
    7
    R
    549
    Python
    7,480

Top repositories

1

Python_Backtesting_Pair-Trading_Strategy

Applied Linear Regression for Trading Business Based Company to Back-test Pair Trading Mean-Reversion Strategy on 200+ stocks using various packages like NSEPY, PANDAS, MATPLOTLIB and many more.
Python
4
star
2

SAS_FINANCE_CROSS_SELLING

Financial Cross-Selling project where the objective is to develop business and market strategies for targeting customers which are more likely to buy insurance products.
SAS
3
star
3

Identify_Apparels_multiLabel_classification_CNN

More than 25% of entire revenue in E-Commerce is attributed to apparels & accessories. A major problem they face is categorizing these apparels from just the images especially when the categories provided by the brands are inconsistent. This poses an interesting computer vision problem which has caught the eyes of several deep learning researchers. Fashion MNIST is a drop-in replacement for the very well known, machine learning hello world - MNIST dataset which can be checked out at ‘Identify the digits’ practice problem. Instead of digits, the images show a type of apparel e.g. T-shirt, trousers, bag, etc. The dataset used in this problem was created by Zalando Research.
Python
3
star
4

SMS-Message-Spam-Detector

Building a machine learning model for spam SMS message classification, then create an API for the model, using Flask, the Python micro framework for building web applications.
Python
2
star
5

search_aggregator

An Assignment task .
Python
1
star
6

Excel-VBA-Macro_Salary_Dashboard

Created automated dashboards for monthly salary databases by using VBA-Macro Code, during a Business Assignment.
1
star
7

R_Loan_Repayment_Prediction

Applied Logistic Regression for Loan Finance Company to predict Loan Repayment status whether the customer is likely to repay or not.
R
1
star
8

Clustering_Airlines_Marketing_segmentation

Applied Clustering technique for An Airlines to find similar groups of customers who belong to it’s frequent flyer program so that Marketing team can target different customer segments with different types of mileage offers.
R
1
star