Nidhi Gangrade

FactualAI

Data Scientist

June 13, 2026 – Present

prediction-model-deployment

October 1, 2020 – October 1, 2020

prediction-model-deployment — GitHub repository

Image_Classification_CNN

March 20, 2020 – March 20, 2020

Given a set of different dog breed images, built an image classifier to determine the breed of a dog in the image.In this project we built traditional CNN, CNN with data augmentation and finally transfer Learning by VGG16 model with weights pre-trained on Imagenet to solve the dog breed classification problem..

FaceRecognition_Keras

March 20, 2020 – March 20, 2020

The Task is to Recognize Faces in the images taken from Pinterest

CNN_DigitRecognition

March 20, 2020 – March 20, 2020

In this notebook, we will build a simple CNN-based architecture to classify the 10 digits (0-9) of the MNIST dataset. The objective of this notebook is to become familiar with the process of building CNNs in Keras. implement all the steps required to build a network - feedforward, loss computation, backpropagation, weight updates etc. We will go through the following steps: Importing libraries and the dataset Data preparation: Train-test split, specifying the shape of the input data etc. Building and understanding the CNN architecture Fitting and evaluating the model

Polynomial_Regression

March 10, 2020 – March 10, 2020

Problem Statement: The objective of the problem is to predict values “current price” attribute from the given features of the Test data. Essentially, the company wants — To identify the variables affecting cars current prices, To create a linear model that quantitatively relates cars current prices with identified significant variables. To know the accuracy of the model, i.e. how well these variables can predict car prices. So interpretation is important!

RandomForest_CreditDefault_Prediction

March 10, 2020 – March 10, 2020

build a random forest model to predict whether a given customer defaults or not. Credit default is one of the most important problems in the banking and risk analytics industry. There are various attributes which can be used to predict default, such as demographic data (age, income, employment status, etc.), (credit) behavioural data (past loans, payment, number of times a credit payment has been delayed by the customer etc.).

RandomForest_AdaBoost

March 10, 2020 – March 10, 2020

In the pronblem given the task is to predict the volume of passengers in trains. This problem is based on MultiClass Classification Problem as the target column has 3 classes : low, medium and high. This Classification problem is best solved using Random Forest Classifier with Boosting Algorithm in order to have better accuracy as well as precision and recall and thus higher f1 score.

Recommandation-System

March 10, 2020 – March 10, 2020

You are the sales manager for "BeerMart", an online beer store in the United States. You want to build a recommendation system (collaborative) for your store, where customers will be recommended the beer that they are most likely to buy.

Logistic-Regression-Decision-Tree--Random-Forest

March 10, 2020 – March 10, 2020

Logistic-Regression-Decision-Tree--Random-Forest — GitHub repository

Clustering-PCA

March 10, 2020 – March 10, 2020

HELP International is an international humanitarian NGO that is committed to fighting poverty and providing the people of backward countries with basic amenities and relief during the time of disasters and natural calamities. It runs a lot of operational projects from time to time along with advocacy drives to raise awareness as well as for funding purposes. After the recent funding programmes, they have been able to raise around $ 10 million. Now the CEO of the NGO needs to decide how to use this money strategically and effectively. The significant issues that come while making this decision are mostly related to choosing the countries that are in the direst need of aid.