Data Science

Hyperparameter tuning using GridSearchCV and RandomizedSearchCV in Python

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In the previous post, we had a brief discussion about the GridSearchCV and RandomizedSearchCV. Now, in this post, we will demonstrate that how we can use the GridSearchCV and RandomizedSearchCV methods available with the Sci-kit learn library for hyperparameter tuning in Python. We will use the sklearn built-in diabetes dataset in this demo. However, if […]

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An introduction to GridSearchCV and RandomizedSearchCV

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In the previous post, we discussed that how we can assess the performance of a Machine learning model using a k-fold cross-validation method. In this post, we will discuss that how we can leverage the GridSearchCV and RandomizedSearchCV methods to find the optimal hyperparameter values. The hyperparameter value is the value that is required before

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Introduction to k-fold Cross-Validation in Python

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This post briefs how we can use the k-fold cross-validation to evaluate a Machine Learning model performance using the Scikit-learn library in Python. We know that the performance of a Machine Learning model depends on the training dataset. Also, if the training dataset has a peculiarity, the model created with that dataset will not work

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Create pair plots using scatter_matrix method in pandas

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The exploratory data analysis is a very important step in a Data Science project. It helps us to visualize the data and identify any hidden trends that might not be visible with summary statistics alone. So, we can use matplotlib and seaborn libraries to create stunning visuals in Python. However, the pandas.plotting module of the

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Plot ECDF in Python

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We know that EDA (Exploratory Data Analysis), is the process of organizing, plotting, and summarizing the data to find trends, patterns, and outliers using statistical and visual methods. Here, we have already discussed various methods of performing EDA with their pros and cons on an underlying dataset. ECDF plot is another visual method of performing

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Relationship between Binomial and Poisson distributions

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In this post, we are going to discuss the Relationship between Binomial and Poisson distributions. We know that Poisson distribution is a limit of Binomial distribution for a large n (number of trials) and small p (independent probability for each trial) values. A large number of trials n with very small probability p indicates a

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Convert Jupyter notebooks to PDF

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Jupyter lab is the next-generation web-based UI experience for Jupyter notebook users. It facilitates a tab-based programming interface that is highly extensible and interactive. It supports 40+ programming languages. We have already discussed how we can use Jupyter notebooks for interactive data analysis with SQL Server. With the help of Jupyter notebooks, we can keep

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Building Decision Tree model in python from scratch – Step by step

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In previous post, we created our first Machine Learning model using Logistic Regression to solve a classification problem. We used “Wisconsin Breast Cancer dataset” for demonstration purpose. Now, in this post “Building Decision Tree model in python from scratch – Step by step”, we will be using IRIS dataset which is a standard dataset that

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Building first Machine Learning model using Logistic Regression in Python – Step by Step

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This post briefs how to create our first machine learning predictive model using Logistic regression in Python. When we start working on a Machine Learning project, first, we perform some data wrangling and transformation to get the tidy dataset. Then, we perform some EDA to find trends, patterns, and outliers in the given dataset. Once, we have machine-interpretable data

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Exploratory Data Analysis (EDA) using Python – Second step in Data Science and Machine Learning

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In the previous post, “Tidy Data in Python – First Step in Data Science and Machine Learning”, we discussed the importance of the tidy data and its principles. In a Machine Learning project, once we have a tidy dataset in place, it is always recommended to perform EDA (Exploratory Data Analysis) on the underlying data

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