Building a Deep Learning Model using Keras

In this post, let us see how to build a deep learning model using Keras. If you haven't installed Tensorflow and Keras, I will show the simple way to install these two modules.

Mastering the Basics of Deep Learning with Illustrations

Deep learning is a powerful machine learning technique. These are widely used in

• Natural Language Processing (NLP)
• image/speech recognition
• robotics
• and many other artificial intelligence projects

ARIMA/SARIMA with Python: Understand with Real-life Example, Illustrations and Step-by-step Descriptions

Autoregressive Integrated Moving Average (ARIMA) is a popular time series forecasting model. It is used in forecasting time series variable such as price, sales, production, demand etc.

Time series Cross-validation and Forecasting Accuracy: Understand with Illustrations & Examples

In this post, let us review

• Standard statistical measures of forecasting accuracy
• Cross-validation in time series
• How to plot forecasts and,
• How to calculate forecasting accuracy in Python

Exponential Smoothing Techniques: Learn with Examples and Illustrations

In this post, let us explore:

• Moving Averages
• Single Exponential Smoothing
• Double Exponential Smoothing
• Triple Exponential Smoothing

Components of Time Series: A Beginner's Visual Guide

In this post, let us explore the four components of time series data.

1. Trend (T)
2. Cyclicality (C)
3. Seasonality (S)
4. Irregular component (I)

Understand Basic concepts of Time Series with Examples and Visual Illustrations

In this post, let us explore the basic concepts about time series. We will also learn about resampling techniques, how to check for stationarity and ways to convert non stationary series into stationary series.