Data Types
Scales of Measurement – Data types: Nominal, Ordinal, Interval and Ratio scale
Blog-posts
ARIMA/SARIMA with Python
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. 1. Basics of ARIMA model As the name suggests, this model involves three parts: Autoregressive part, Integrated and Moving Average part. Let us explore these parts one by …
Time Series Components
Components of Time Series In this post, let us explore the four components of time series data. Trend (T) Cyclicality (C) Seasonality (S) Irregular component (I) Let us look at these components one by one. Trend (Secular Trend) Trend is long term movement of the time series. Trend can be increasing or decreasing or absent …
Missing Values
Handling Missing Values in Python In this post, we will discuss: How to check for missing values Different methods to handle missing values Real life data sets often contain missing values. There is no single universally acceptable method to handle missing values. It is often left to the judgement of the data scientist to whether …
Pre-processing
Data Preprocessing – Creating Dummy Variables and Converting Ordinal Variables to Numbers with Examples Data cleaning is a critical step before fitting any statistical model. It includes: Handling missing values Handling outliers Transforming nominal variables to dummy variables (discussed in this post) Converting ordinal data to numbers (discussed in this post) Transformation (discussed in this …
Confusion Matrix
Confusion Matrix, Accuracy, Precision, Recall, F score explained with an example In this post, we will learn about What is accuracy What are precision, recall, specificity and F score How to manually calculate these measures How to interpret these measures What is confusion matrix and how to construct it What is the AUC score and …
Building a Deep Learning Model
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. 1. Installing Tensorflow and Keras Open Anaconda Navigator. Under Environments, create new environment in Python …
Deep Learning Basics
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 What is Deep Learning? A model which consists of more than three layers in a neural network model is a deep learning model. More than three layers means one …