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credit-risk-modeling

credit-risk-modeling-using-machine-learning

A study and comparison of Risk Modeling algorithms (Capstone Project)

credit-risk-modelling

Credit Risk analysis by using Python and ML

credit_risk_evaluation

This repository contains an approach (developed in Python) to credit risk analysis. The dataset was provided by a famous startup bank.

creditanalytics-loan-prediction

A predictive model that uses several machine learning algorithms to predict the eligibility of loan applicants based on several factors

cryptocurrency-data-collection-using-api

Using API, Collected Price data of Cryptocurrencies. Softwares used Python, libraries used Pandas, Numpy, Matplotlib, Glob.

cs221_ai

🥚 Stanford CS221: Artificial Intelligence: Principles and Techniques

cs228

Code for Stanford CS228: Probabilistic Graphical Models

cs7646-machine-learning-for-trading

Assignments as part of CS 7646 at GeorgiaTech under Dr. Tucker Balch in Fall 2017

databaseexercises2

Independent study with databases using SQL

datacamp-3

DataCamp data-science courses

deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

deep_learning

In this repo, all my deep learning projects are there

dimesnsionality-reduction

drop

Fixed Income Analytics, Portfolio Construction Analytics, Transaction Cost Analytics, Counter Party Analytics, Asset Backed Analytics

evolopy

evolutionary-machine-learning

expected-credit-loss

Lifetime Expected Credit Loss calculation under IFRS 9

financial-analytics

MSCA 32001 Financial Analytics - Finance projects in R

financial-engineering-baruchmfe-cpp

My solutions for the “C++ Programming for Financial Engineering” Online Certificate. It is a joint project by the Baruch MFE program, Dr. Daniel Duffy and QuantNet.

finart.ai

AI cases in Finance

fxcm_currency

Using Machine Learning for live currency trading

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

home-credit-default-risk

Objective of this competition is to use historical loan application data to predict whether or not an applicant will be able to repay a loan.

housing_price_prediction_king_county_usa

In this project, I have predicted Housing sales price prices for King County,USA which includes Seattle. It includes homes sold between May 2014 and May 2015. It has 19 house features plus the price and the id columns, along with 21613 observations. In this project I have done the implementation of different Boosting regression machine learning models such as Gradient Boosting, eXtreme Gradient Boosting (XGB) and Adaboost. In this project, I have also used Permutation Importance for filtering the irrelevant features of the dataset. In this project, I have predicted Housing sales price prices for King County,USA which includes Seattle. It includes homes sold between May 2014 and May 2015. It has 19 house features plus the price and the id columns, along with 21613 observations. In this project I have done the implementation of different Boosting regression machine learning models such as Gradient Boosting, eXtreme Gradient Boosting (XGB) and Adaboost. In this project, I have also used Permutation Importance for filtering the irrelevant features of the dataset. Maximum Accuracy achieved around 98.59%.

integrated-credit-modeling-ccar-to-cecl

• Calculated the Capital Ratios,Risk Weighted Assets, Capital requirement over projected time horizon for both CCAR and CECL. • Created PD model using Time Series,Logistic regression,Random Forests,Neural Networks,Markov transition Matrix. • Software used various SAS 9.4, Python.

intro-to-probability-solutions

Solutions to the exercises in Grinstead and Snell's Introduction to Probability

k-means-clustering-and-factor-analysis-of-credit-card-data

kaggle_loan_default_prediction

R code for Kaggle's Loan Default Prediction - Imperial College London challenge

learn_computer_science_in_5_months

This is the Curriculum for "Learn Computer Science in 5 Months" By Siraj Raval on Youtube