Embedded Files
Market Sentiment, Summarizer and Predictor
Market Sentiment, Summarizer and Predictor
Takes User Input for: General News Topics Company name & Ticker (Dow Jones) Summarizes Top Headlines Provides Sentiment of News Articles Provides Directionality Prediction of Company specific stocks Provides links to top news articles
Stock News Sentiment Analysis using NLTK and BERT
Stock News Sentiment Analysis using NLTK and BERT
In the notebook, I have scraped the website, FinViz, to get the news articles associated with a company's stock. I have calculated the sentiment of each of the stocks and have plotted them.
Image Classification using Convolutional Neural Network
Image Classification using Convolutional Neural Network
In the notebook, I have performed image classification on the Alien/Predator Dataset. I have built a convolutional neural network, trained it by tuning the hyperparameters and have used it to classify the images with an accuracy of more than 75%. I have loaded the data set in this Notebook, built a model, trained it, plotted the training progression and predicted using the validation dataset, if the image is that of an alien or predator.
Image Generation using AE, VAE and GAN
Image Generation using AE, VAE and GAN
In this project, I have developed an AE (Auto-Encoder), VAE (Variational Auto-Encoder), GAN (Generative Adversarial Network). I have used the Keras package from TensorFlow library to develop the systems. I have used the Fashion MNIST dataset to train the networks and generate new images.
House price prediction using Regression Algorithms on Boston Housing Dataset
House price prediction using Regression Algorithms on Boston Housing Dataset
In the notebook, I have applied multiple regression algorithms on the Boston Housing Dataset. I have compared each of them and have tabulated the results and discussed the features.
Neural Network from Scratch
Neural Network from Scratch
In the following Notebook, I have developed a neural network from scratch (only numpy) without using any pre-defined packages. I have implemented a Logistic Regression Model, tested it on 2 data sets, developed a shallow Neural Network (with 1 hidden layer) and implemented further improvements on the aforementioned Neural Network. I have added L2 regularization on the shallow neural network to improve its performance.
Credit Card Fraud Detection
Credit Card Fraud Detection
In this notebook, I have developed a machine learning algorithm to identify credit card frauds. In the notebook, I have used the credit card fraud data from Kaggle. This data was compiled in 2013 from European users.
Market Index Forecasting Model
Market Index Forecasting Model
The idea that the stock market is volatile is not new. Rather it is a myth that has percolated over the ages. In fact speculative bubbles have been existing in the stock market since 1637, when the price of Tulip went so high in the Netherlands that when it crashed it sent a nation into a tizzy . In this paper, I attempt to pull back the curtains, and figure out how the High Value in the stock market is dependent on the Open Value, Low Value, Close Value. Once that has been done, we will attempt to forecast a model of how the market would act over the next few cycles. We will be using the RStudio to implement the project, in the R programming language. Using R, we will be predicting the maximum and the minimum possible value, that the BSE SENEX can hit in the next cycle.
Market Index Forecasting Model.pdf
Diabetes Forecasting Model
Diabetes Forecasting Model
My mother has been a diabetic for the last 15 years of her life. I have known the difference between the Fasting and BP sugar levels for a long time. Therefore, when I found a public data set of the diabetes levels against age, blood pressure, and BMI, it got me thinking if I could map the relationship between the multiple factors and figure out how these factors can have an impact on the blood sugar levels. In this paper, I attempt to map the relation between the multiple factors, affecting the blood sugar levels. I will be using the R Studio, using the R Programming language to implement the project
My mother has been a diabetic for the last 15 years of her life. I have known the difference between the Fasting and BP sugar levels for a long time. Therefore, when I found a public data set of the diabetes levels against age, blood pressure, and BMI, it got me thinking if I could map the relationship between the multiple factors and figure out how these factors can have an impact on the blood sugar levels. In this paper, I attempt to map the relation between the multiple factors, affecting the blood sugar levels. I will be using the R Studio, using the R Programming language to implement the project
Diabetes Prediction Model.pdf Social Inclusion through Digital Inclusion
Social Inclusion through Digital Inclusion
IIM Calcutta Internship.pdfI worked as an Intern on the project, "Social Inclusion through Digital Inclusion", under Indian Institute of Management, Calcutta from 01/02/2016 to 31/03/2016. I worked in implementing an online learning system (much before online learning was the most important thing in the world), named "OwlishOracle". I worked with a group of elderly teachers and training them in using the platform, to act as a bridge in remotely connecting elderly teachers to underprivileged students. I also contributed in re-structuring the learning materials for science in secondary level, using online resources.
Page updated
Google Sites
Report abuse