Vikram Mathur (@VikramMathur3012)
github

VikramMathur3012

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  • Stars
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    22
  • Global Rank 603,566 (Top 21 %)
  • Followers 1
  • Registered almost 5 years ago
  • Most used languages
    Jupyter Notebook
         88.9 %
    PLpgSQL     11.1 %
  • Location πŸ‡¬πŸ‡§ United Kingdom
  • Country Total Rank 21,374
  • Country Ranking
    PLpgSQL     66
    Jupyter Notebook
         968

Top repositories

1

Lead-Scoring

Build a logistic regression model to assign a lead score between 0 and 100 to each of the leads which can be used by the company to target potential leads. A higher score would mean that the lead is hot, i.e. is most likely to convert whereas a lower score would mean that the lead is cold and will mostly not get converted.
Jupyter Notebook
4
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2

Telecom-Churn

Analyse customer-level data of a leading telecom firm, build predictive models to identify customers at high risk of churn and identify the main indicators of churn.
Jupyter Notebook
3
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3

House-Price-Prediction

Build a regression model using regularisation in order to predict the actual value of the prospective properties and decide whether to invest in them or not.
Jupyter Notebook
3
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4

Big-Data-Hive-and-SQL

Hive and SQL Files
PLpgSQL
2
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5

Credit-Card-Fraud

Predict fraudulent credit card transactions with the help of machine learning models. Handling highly imbalanced data (using Random Oversampling, SMOTE, ADASYN) and training multiple models (Logistic Regression, K-Nearest Neighbours, Decision Tree, Random Forest and XG Boost) to see the best performance
Jupyter Notebook
2
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6

Countries-Socio-Economic-Need-NGO

Choosing the countries that are in the direst need of NGO aid based on the $10 million fund. Categorising the countries using some socio-economic and health factors that determining the overall development of the country. Suggest the countries which the CEO needs to focus on the most. Using Clustering and Principal Component Analysis techniques
Jupyter Notebook
2
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7

data-science

Machine Learning Algorithm repository. Linear Regression, Logistic Regression, Decision Tree, Random Forest, XG Boost, Clustering and PCA etc.
Jupyter Notebook
2
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8

Car-Price-Prediction-Linear-Regression

Modelling the price of cars with the available independent variables. It will be used by the management to understand how exactly the prices vary with the independent variables. They can accordingly manipulate the design of the cars, the business strategy etc. to meet certain price levels. Further, the model will be a good way for management to understand the pricing dynamics of a new market.
Jupyter Notebook
2
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9

GDP-Analysis

Exploratory Data Analysis - Analyse and compare the GDPs of various Indian states (both total and per capita). Top-level recommendations to the Chief Ministers (CMs) of various states which will help them prioritize areas of development for their respective states.
Jupyter Notebook
2
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