This is a beginner-friendly end-to-end project for Machine Learning. The only prerequisite of the project is to know Python. Other than it, everything is covered in the project itself.
Perks of this project
In this project, we will learn how to predict images from their noisy version. We will use the MNIST dataset for this project. First, we will load the dataset, explore it, and they we will learn how to introduce noise to an image. Next we will train a KNN Classifier to predict the original image from it's noisy version.
Skills you will develop:
Data analysis is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, drawing conclusions, and supporting decision-making.
The steps to perform Data Analysis depends on the end goal we want to pursue such as to drive business decisions, evaluate performance, for making predictions, etc.
In this tutorial, we will perform Data Analysis with the end goal of feeding the data to a Machine Learning model i.e for making predictions.
This is a beginner-friendly end-to-end project for Data Analysis. The only prerequisite of the project is to know Python. Other than it, everything …
In any machine learning project, 90% of work is about data extraction, cleaning, preprocessing. This is a very challenging part of the machine learning projects. This skill is must have for any machine learning engineer.
Solve these problems to become very efficient at solving data preprocessing, cleaning, transforming, or extracting using Pandas, Python, and Numpy.