By Dr. Shripad Bhat, Data Scientist September 4, 2019 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 …
By Dr. Shripad Bhat, Data Scientist September 4, 2019 Time Series – Basic concepts Resampling: A) Downsampling In simple terms, it is like aggregating. For example: converting daily data to monthly data, or quarterly data to yearly data etc. In the following example, I have converted daily data to weekly data. B) Upsampling Here we …
By Dr. Shripad Bhat, Data Scientist September 4, 2019 Importing data into Python In this post, we will learn: How to import data into python How to import time series data How to handle different time series formats while importing A) Importing Normal Data Suppose you have a data file saved in csv format on …
By Dr. Shripad Bhat, Data Scientist September 4, 2019 Principal Component Analysis (PCA) explained with examples In this post, let us understand What is Principal Component Analysis (PCA) When to use it and what are the advantages How to perform PCA in Python with an example What is Principal Component Analysis (PCA)? Principal Component …
By Dr. Shripad Bhat, Data Scientist September 4, 2019 In this post, let us explore: Random Forest When to use Advantages Disadvantages Hyperparameters Examples Random Forest When to use Random forest can be used for both classification and regression tasks. If the single decision tree is over-fitting the data, then random forest will help in …
By Dr. Shripad Bhat, Data Scientist September 4, 2019 In this post, let us explore: Ensemble Models Bagging Boosting Stacking Ensemble Models/Methods/Learning Ensembling is clubbing predictions from different models to get better performance. How to club different predictions from different models to get a single prediction? There are different ways of doing it. Bagging Boosting …
By Dr. Shripad Bhat, Data Scientist September 4, 2019 Logistic regression is a supervised learning technique applied to classification problems. In this post, let us explore: Logistic Regression model Advantages Disadvantages Example Hyperparemeters and Tuning Logistic Regression model Logistic functions capture the exponential growth when resources are limited (read more here and here).Sigmoid function is a special case …
By Dr. Shripad Bhat, Data Scientist September 4, 2019 Support Vector Machines (SVM) Suppose there are two independent variables (features): x1 and x2. And there are two classes Class A and Class B. The following graphic shows the scatter diagram. If want to partition these two classes using a line (or hyperplane), the green hyperplane …
