1.3 Setting Google Colab
1.4 Loading data
2.1 Line Plot
2.2 Area Plot
2.3 Bar Plot
4. Regression For Forecasting
This course is divided into four modules whose topics are displaced at the left sidebar. All the lecture are explained in video and also written in blog for self-paced. Please find the data and the Google colab notebook for your reference.
Module -1 : Time Series Analysis:
In this module you will learn about the forecasting and how it is different from regression analysis. At the same time you will also learn about the time series components like “Trend”, “Cyclicality”, “Seasonality” and “Irregularity” and with learn the difference in the components with an stock mark data example. Then you will learn about setting up of Google Colab and also show you to load the data from your Google Drive. Find the urls below to download data and notebook and also watch YouTube video lecture in english and telugu.
In this module, we will explain how to visualize time series data. In general, there are four kinds of charts that are used to visualize time series data. Here in this modules we explain how to plot “line chart” , “area chart”, “bar chart” and “Heatmaps”. Here we will code all the visualization using seaborn and pandas library. This module is very important module where we can able to analyze the time series data even without model. Find the urls below to download the data and colab notebook.
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Module -3 , Module-4, Module-5, Module -6, Module-7, Module-8, Module-9, Module-10, Module-11, Module-12