End-to-End ML Project- Beginner friendly

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Installing Libraries

First, you'll need to install several libraries and their dependencies which you'll require in the project. The basic libraries which we need generally in every project are-

  1. numpy- Its main functionality includes working with arrays and performing various mathematical operations on arrays in an efficient manner.

  2. pandas- Its main functionality includes data manipulation and analysis. Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. It is built on top of numpy.

  3. matplotlib- Its main functionality includes visualizing data. It's built on top of numpy.

  4. sklearn- It is the most useful and robust library for machine learning in python. You can think of a task in machine learning modeling, and there will be a function performing that task in sklearn. It supports both supervised and unsupervised learning. It provides various tools for model fitting, data preprocessing, model selection, model evaluation, and many other utilities. It's built on top of pandas, numpy, and matplotlib.

But CloudxLab already has pre-installed libraries. So, you don't need to worry about this step.


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