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bbc-frontend-clone

Just a try to clone the frontend design of BBC's news webpage

best-ad-selection-thompson-sampling

Model based on reinforcement learning to solve a form of multi-armed bandit problem.

best-ad-selection-upper-confidence-bound

Model based on reinforcement learning to solve a form of multi-armed bandit problem.

cats-vs-dogs-classification-cnn

Convolutional Neural Network to classify the given images of cats and dogs.

cavegame-shelve

Using the Shelve module to store the data on a file in binary format so that it can be read back whenever required.

churn-modelling-ann

Model to predict the customer's likelihood of stopping the usage of services of a bank.

classification-template

Template for easy classification model development.

clustering-hierarchical

Model to cluster customers of a mall into different clusters with the help of their personal informations. Useful for understanding the customers better.

clustering-k-means

Model to cluster customers of a mall into different clusters with the help of their personal informations. Useful for understanding the customers better.

clustering-template

Template for easy clustering model development.

csit073_fy_project

customer-classification-for-ads-decision-tree

Model to classify customers (on the basis of their personal information) as more likely or less likely to buy a product.

customer-classification-for-ads-k-nn

Model to classify customers (on the basis of their personal information) as more likely or less likely to buy a product.

customer-classification-for-ads-kernel-svm

Model to classify customers (on the basis of their personal information) as more likely or less likely to buy a product.

customer-classification-for-ads-logistic-regression

Model to classify customers (on the basis of their personal information) as more likely or less likely to buy a product.

customer-classification-for-ads-naive-bayes

Model to classify customers (on the basis of their personal information) as more likely or less likely to buy a product.

customer-classification-for-ads-random-forest

Model to classify customers (on the basis of their personal information) as more likely or less likely to buy a product.

data-preprocessing

Some of the mostly used data preprocessing steps before training a model.

dimensionality-reduction-kernel-pca

Use of PCA with kernel to reduce the dimension of a dataset to 2D so as to facilitate the vizualization of our model.

dimensionality-reduction-lda

Use of Linear Discriminant Analysis to reduce the dimension of a dataset to 2D so as to facilitate the vizualization of our model.

dimensionality-reduction-pca

Use of Principle Component Analysis to reduce the dimension of a dataset to 2D so as to facilitate the vizualization of our model.

fuse_training

fuse_training_balot_classification

gamecharacters-oop

Using features of OOP like inheritance, getters and setters and overriding in Python.

generators

Use of Generators in Python

htmldoc-oop

Using inheritance and composition in OOP in Python.

k-fold-cv-and-hyperparameter-tuning

Use of K-Fold cross-validation and grid search for hyperparameter tuning.

leapfrog

manim

Animation engine for explanatory math videos

market-basket-optimization-apriori

Model to suggest how the products in a supermarket must be placed so as to maximize the sales. Based on associative rule learning, this model can also be used to suggest the customers what products they might be interested in.