Early diabete prediction using XGBoost on AWS

In this article, we will use again the same dataset that we have used in previous articles to do a an early diabete prediction but with its libsvm format which is made available on this link. This time, we will use XGBoost which has shown many advantages like parallel processing, faster convergence, possibility of cross-validationContinue reading Early diabete prediction using XGBoost on AWS

Price Optimization using Statistical Regression

In this article, we will use statistic method to implement a price optimization using regression algorithm called Ordinary Least Square which is available on the statsmodel library. You can use any other machine learning regression algorithm like XGboost but I have chosen OLS as it provides substantial information relevant to price optimization like the R-squaredContinue reading Price Optimization using Statistical Regression

Multivariate Time Series Forecasting using Encoder-Decoder

In this post, you will see how to implement a multivariate time series forecasting using Encoder – Decoder deep learning architecture. Once again, the dataset is taken from ICU Machine Learning repository. Briefly, as the site says : “the dataset contains 9358 instances of hourly averaged responses from an array of 5 metal oxide chemicalContinue reading Multivariate Time Series Forecasting using Encoder-Decoder

Sentiment analysis using Keras and Tensorflow

Sentiment analysis is actually one of the hottest topics in Deep learning area. It falls under the umbrella of NLP. Companies use sentiment analysis for product analytics, brand monitoring and many other applications. In this tutorial, you will discover how to develop sentiment analysis model using Deep Learning, specifically RNN. Once again, we will useContinue reading Sentiment analysis using Keras and Tensorflow