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 […]
In this post “Interactive Data Analysis with SQL Server using Jupyter Notebooks“, we will demonstrate how we can use Jupyter Notebooks for interactive data analysis with SQL Server. Jupyter notebooks are one of the most useful tools for any Data Scientist/Data Analyst. It supports 40+ programming languages and facilitates web-based interactive programming IDE. We can
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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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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
Most of the Data Science / Machine Learning projects follow the Pareto principle where we spend almost 80% of the time in data preparation and remaining 20% in choosing and training the appropriate ML model. Mostly, the datasets we get to create Machine Learning models are messy datasets and cannot be fitted into the model
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