Author Archives: Yugesh Verma
dense layer is deeply connected layer from its preceding layer which works for changing the dimension of the output by performing matrix vector multiplication
The post Dense Layers in Neural Networks appeared first on Analytics India Magazine.
Time series analysis, is one of the major parts of data science and techniques like clustering, splitting and cross-validation require a different kind of understanding of the data. In one of our articles, we have discussed the clustering of time series. In this article, we are going to discuss cross-validation in time series. The major […]
The post How to improve time series forecasting accuracy with cross-validation? appeared first on Analytics India Magazine.
Time series analysis, is one of the major parts of data science and techniques like clustering, splitting and cross-validation require a different kind of understanding of the data. In one of our articles, we have discussed the clustering of time series. In this article, we are going to discuss cross-validation in time series. The major […]
The post How to improve time series forecasting accuracy with cross-validation? appeared first on Analytics India Magazine.
To make a better explanation of ARIMA we can also write it as (AR, I, MA) and by this, we can assume that in the ARIMA, p is AR, d is I and q is MA.
The post Quick way to find p, d and q values for ARIMA appeared first on Analytics India Magazine.
There are a few approaches that can be used to reduce the training time time of neural networks.
The post 7 tricks to speed up the training of a neural network appeared first on Analytics India Magazine.
Through this post we will discuss about overfitting and methods to use to prevent the overfitting of a neural network.
The post 5 methods that will not let your neural network model overfit appeared first on Analytics India Magazine.
Detecting outliers in the categorical data is something about the comparison between the percentage of availability of data for all the categories.
The post How to detect and treat outliers in categorical data? appeared first on Analytics India Magazine.
ARIMA is the most popular model used for time series analysis and forecasting. Despite being so popular among the community, it has certain limitations as well.
The post 5 conditions when the ARIMA model should be avoided appeared first on Analytics India Magazine.
The exponential smoothing and moving average are the two basic and important techniques used for time series forecasting.
The post Exponential smoothing vs Moving average for time series forecasting appeared first on Analytics India Magazine.
The exponential smoothing and moving average are the two basic and important techniques used for time series forecasting.
The post Exponential smoothing vs Moving average for time series forecasting appeared first on Analytics India Magazine.