AI/ML, Data Science

Heatmap

Heatmap depicts the two-dimensional data (matrix form) in the form of graph. Data requirement: Data can be in the form of: Matrix such as correlation matrix Or a pandas cross tabulated dataframe Example: Importing the data Cross-tabulate the data using pd.crosstab Plot the heatmap using seaborn library  Add linewidths (width of line dividing each cell …

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Importing-Data

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 your computer. How to import this into Python? I saved …

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Train-Test split

Train-Test split and Cross-validation Building an optimum model which neither underfits nor overfits the dataset takes effort. To know the performance of our model on unseen data, we can split the dataset into train and test sets and also perform cross-validation. Train-Test split To know the performance of a model, we should test it on unseen data. For …

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Bias-Variance Tradeoff

Occam’s Razor, Bias-Variance Tradeoff, No Free Lunch Theorem and The Curse of Dimensionality In this post, let us discuss some of the basic concepts/theorems used in Machine Learning: Occam’s Razor (Law of Parsimony) What is Bias-variance Tradeoff No Free Lunch Theorem The curse of dimensionality Occam’s Razor (Law of Parsimony) William of Ockham was a …

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Exploratory Data Analysis

“A picture is worth a thousand words” A complex idea can be understood effectively with the help of visual representations. Exploratory Data Analysis (EDA) helps us to understand the nature of the data with the help of summary statistics and visualizations capturing the details which numbers can’t. In this post, let us explore Visualizing the data  …

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Data Types

Scales of Measurement – Data types: Nominal, Ordinal, Interval and Ratio scale

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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 …

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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 …

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