Niranjankumar-c/CreditRiskAnalytics

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Created about 6 years ago
Updated over 5 years ago

Niranjankumar-c/CreditRiskAnalytics

Niranjankumar-c

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Predicting the default customers

DeepLearning-PadhAI

All the code files related to the deep learning course from PadhAI

Jupyter Notebook

GradientDescent_Implementation

Implement different variants of gradient descent in python using numpy

Jupyter Notebook

Feedforward_NeuralNetworrks

Build our neural networks from scratch

Jupyter Notebook

Perceptron_Model

The repository contains the implementation of perceptron model.

Jupyter Notebook

CustomerSegmentation-Banking

Develop a customer segmentation to define marketing strategy. Used PCA to reduce dimensions of the dataset and KMeans++ clustering technique is used for clustering and profiling of clusters.

Jupyter Notebook

LeadGeneration

Lead generation is a challenge that businesses have faced since the dawn of capitalism.

Jupyter Notebook

Complete_Python-3_BootCamp_Advanced

Learn Python with projects covering game & web development, web scraping, MongoDB, Django, PyQt, and data visualization

Jupyter Notebook

DeepLearning-Pytorch-IBM

Deep Learning with Python and PyTorch IBM Edx Course

Jupyter Notebook

PriceOptimization

Analyzing different pricing methodologies

Jupyter Notebook

TelecomChurn

Analysing the telecom customer churn data

Jupyter Notebook

DataScienceBlogAnalysis_NLP

Code to Scrap the Blog content and Analyze using NLP

Jupyter Notebook

HRAnalyticsEmployeeAttrition

Uncover the factors that lead to employee attrition using IBM Employee Data

Jupyter Notebook

DataAnalytics_using_ClickstreamData

Casestudy completed as part of BigData training from analytix labs

DeepLearning_A-Z_NeuralNetworks_Python

Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts

Jupyter Notebook

CreditCardSpendPrediction_Regression

Predicting the drivers affecting the credit card spending

Jupyter Notebook

OverFitting

Analyse OverFitting of data

AnalyzingStockData

Exploratory Data Analysis of bank stock prices

Jupyter Notebook

SqoopCaseStudy-ALabs

Sqoop Case Study's done during Analytixlabs Dig Data Classes

PredictBuildingDamage_MLChallenge

Determining the degree of damage that is done to buildings post an earthquake using Machine Learning.The damage to a building is categorized in five grades. Each grade depicts the extent of damage done to a building post an earthquake.

Jupyter Notebook