aadimangla

Churn-Modelling-for-a-Bank

A churn model is a mathematical representation of how churn impacts your business. Churn calculations are built on existing data (the number of customers who left your service during a given time period). A predictive churn model extrapolates on this data to show future potential churn rates.

Color_detection-Model

Detecting colors in an image using opencv.

Custom-Trained-Recurrent-Neural-Network

Using high-level frameworks like Keras, TensorFlow or PyTorch allows us to build very complex models quickly. However, it is worth taking the time to look inside and understand underlying concepts. Not so long ago I published an article, explaining — in a simple way — how neural nets work. However, it was a highly theoretical post, dedicated primarily to math, which is the source of the NN superpower. From the beginning, I was planning to follow-up on this topic in a more practical way. This time we will try to utilize our knowledge and build a fully operational neural network using only NumPy.

Customer-Service-Bot

Customer service bot is a bot that uses artificial intelligence (AI) and machine learning to answer basic customer questions via a business messenger. It can recognize and answer multiple forms of the same question and can be trained to give instant responses using your preferred voice or text.

IMDB-Movie-Reviews-Sentiment-Analysis

It analyses the movie review entered by a user for any specific movie and analyses what is the sentiment of the review. It helps the companies rate the movie and understand crowd sentiment regarding it. Sentiment analysis is a natural language processing problem where text is understood and the underlying intent is predicted.

Mall-Customer-Segmentation

Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways. You can provide different value propositions to different customer groups. Customer segments are usually determined on similarities, such as personal characteristics, preferences or behaviours that should correlate with the same behaviours that drive customer profitability.

Market-Basket-Optimization

Market Basket Analysis What is it? Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items. For example, if you are in an English pub and you buy a pint of beer and don't buy a bar meal, you are more likely to buy crisps (US. chips) at the same time than somebody who didn't buy beer.

Predicting-product-sales-through-ads

In simpler words we tell whether a user on Social Networking site after clicking the ad’s displayed on the website,end’s up buying the product or not. This could be really helpful for the company selling the product. Lets say that its a car company which has paid the social networking site(For simplicity we’ll assume its Facebook from now on)to display ads of its newly launched car.Now since the company relies heavily on the success of its newly launched car it would leave no stone unturned while trying to advertise the car. Well then whats better than advertising it on the most popular platform right now.But what if we only advertise it to the correct crowd.

Restaurant-Reviews-Sentiment-Analysis

It analyses the review of the food and services of the restaurant entered by a user for any specific restaurant and analyses what is the sentiment of the review. It helps the companies rate the movie and understand crowd sentiment regarding it. Sentiment analysis is a natural language processing problem where text is understood and the underlying intent is predicted.

Conjexure-A-Web-App-for-Stock-Market-Forecasting

Conjexure is a machine learning web app for forecasting the stock prices of certain companies into the future.

aadimangla/Customer-Service-Bot

Customer service bot is a bot that uses artificial intelligence (AI) and machine learning to answer basic customer questions via a business messenger. It can recognize and answer multiple forms of the same question and can be trained to give instant responses using your preferred voice or text.

aadimangla/Market-Basket-Optimization

Market Basket Analysis What is it? Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items. For example, if you are in an English pub and you buy a pint of beer and don't buy a bar meal, you are more likely to buy crisps (US. chips) at the same time than somebody who didn't buy beer.

aadimangla/Mall-Customer-Segmentation

Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways. You can provide different value propositions to different customer groups. Customer segments are usually determined on similarities, such as personal characteristics, preferences or behaviours that should correlate with the same behaviours that drive customer profitability.

aadimangla/Predicting-product-sales-through-ads

In simpler words we tell whether a user on Social Networking site after clicking the ad’s displayed on the website,end’s up buying the product or not. This could be really helpful for the company selling the product. Lets say that its a car company which has paid the social networking site(For simplicity we’ll assume its Facebook from now on)to display ads of its newly launched car.Now since the company relies heavily on the success of its newly launched car it would leave no stone unturned while trying to advertise the car. Well then whats better than advertising it on the most popular platform right now.But what if we only advertise it to the correct crowd.

aadimangla/IMDB-Movie-Reviews-Sentiment-Analysis

It analyses the movie review entered by a user for any specific movie and analyses what is the sentiment of the review. It helps the companies rate the movie and understand crowd sentiment regarding it. Sentiment analysis is a natural language processing problem where text is understood and the underlying intent is predicted.

aadimangla/Churn-Modelling-for-a-Bank

A churn model is a mathematical representation of how churn impacts your business. Churn calculations are built on existing data (the number of customers who left your service during a given time period). A predictive churn model extrapolates on this data to show future potential churn rates.

aadimangla/Restaurant-Reviews-Sentiment-Analysis

It analyses the review of the food and services of the restaurant entered by a user for any specific restaurant and analyses what is the sentiment of the review. It helps the companies rate the movie and understand crowd sentiment regarding it. Sentiment analysis is a natural language processing problem where text is understood and the underlying intent is predicted.

aadimangla/Color_detection-Model

Detecting colors in an image using opencv.

aadimangla/course-nlp

A Code-First Introduction to NLP course

aadimangla/Custom-Trained-Recurrent-Neural-Network

Using high-level frameworks like Keras, TensorFlow or PyTorch allows us to build very complex models quickly. However, it is worth taking the time to look inside and understand underlying concepts. Not so long ago I published an article, explaining — in a simple way — how neural nets work. However, it was a highly theoretical post, dedicated primarily to math, which is the source of the NN superpower. From the beginning, I was planning to follow-up on this topic in a more practical way. This time we will try to utilize our knowledge and build a fully operational neural network using only NumPy.

aadimangla/Fashion-Mnist-Model

Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. We intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.

aadimangla/Handwritten-Digit-Classification

The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image. It is a good database for people who want to try learning techniques and pattern recognition methods on real-world data while spending minimal efforts on preprocessing and formatting.

aadimangla/Naaniz_chatbot

aadimangla/Poetry-Generator

Automatically generate imaginative poetry using your own ideas. It generates poetry with resemblance to Shakespeare's poetry by only taking a line or words as an input from the user. It has proven to give quite good poems.

aadimangla/Sarcasm-Detector

t analyses the text enterd by a user and analyses whether the text is sarcastic or not. Sarcasm, which is both positively funny and negatively nasty, plays an important part in human social interaction. Sarcasm detection is a very narrow research field in NLP, a specific case of sentiment analysis where instead of detecting a sentiment in the whole spectrum, the focus is on sarcasm. Therefore the task of this field is to detect if a given text is sarcastic or not.

aadimangla/Software

aadimangla/Software-1

aadimangla/template

GitHub Repository Template for Data Science Community SRM.

aadimangla/aadimangla

aadimangla/app-dam-vs-pond

aadimangla/awesome-github-profile-readme-templates

This repository contains best profile readme's for your reference.

aadimangla/codersgyan

aadimangla/Dictionary-Website

aadimangla/Keeper-App

aadimangla/microservices-config

The contains configurations for springboot microservices

aadimangla/OCR

aadimangla/opencv

Open Source Computer Vision Library

aadimangla/Realtime-Patisserie-App

aadimangla/StumbleUpon-Evergreen-Classification-Challenge

StumbleUpon Evergreen Classification Kaggle Challenge

aadimangla/User-Management-System