Rittika Sur's repositories
Customer-Churn-prediction-using-Simple-ANN
Customer churn prediction is to measure why customers are leaving a business. We will build a deep learning model to predict the churn.
Detection-of-moving-object
Detection of moving objects in a video i.e. car, human, etc using opencv with 2 different methods.
Sentimental-Analysis-using-LSTM-GRU
Sentiment analysis lets you analyze the sentiment behind a given piece of text. In this notebook, we have done sentimental analysis for amazon shoe reviews, using 2 RNN models(LSTM and GRU)
Stock-Prediction-using-web-scrapping
The problem we are targeting here is to predict the future value of S&P500 given the past values. The key is to predict the value faster with increased accuracy in comparison to classical techniques. Here we used techniques in deep learning called Long-Short Term Memory(LSTM) that is used to learning the pattern occurring in temporal data. This learning is then used to predict the future movement of the data.
Text-based-editing-using-speech-recognition
Using voice to control notepad for text editing.
Text-Extraction-using-Pytesseract
Text extraction from image using pytessearct. An API is built using flask and docker.
Working-with-librosa
Librosa is a package in python that deals with audio clips like converting then into frequencies using FFT or converting them to spectogram.