Machine Learning

MNIST: MNIST ( M odified N ational I nstitute of S tandards and T echnology ): ·        MNIST dataset , ·        which is a set of 70,000 small images of digits handwritten by ü   high school students ü   employees of the US Census Bureau . Each image is labeled with the digit it represents. Figure 1. Digits from the MNIST dataset   ·        This set has been studied so much that it is often called the “ hello world ” of Machine Learning : ü   whenever people come up with a new classification algorithm , ü   they are curious to see how it will perform on MNIST , and ü    anyone who learns Machine Learning tackles this dataset sooner or later.   ü   Scikit-Learn provides many helper functions to download popular datasets . ü   MNIST is one of them. •         The following code fetches the MNIST dataset : from sklearn.datasets import fetch_openml MNIST = fetch_openml ( 'MNIST_784' , version = 1 ) MNIST . keys () •         dict_keys(['data', 'target'

  How Machine Learning Works? YouTube Video Link:  https://www.youtube.com/watch?v=uGe7TYdMF64&t=6s

  What is Machine Learning •         “ Machine Learning •         enables a Machine to Automatically learn from Data , •         improve performance from an Experience and •         predict things without explicitly programmed .” •         In Simple Words, when we fed the Training Data to Machine Learning Algorithm, ü   this algorithm will produce a mathematical model and ü   with the help of the mathematical model , ü   the machine will make a prediction and ü   take a decision without being explicitly programmed. ·        Also, during training data , o    the more machine will work with it o    the more it will get experience and o    the more efficient result is produced . Example:   In Driverless Car , the training data is fed to an Algorithm like   ü   how to Drive a Car on Highway, Busy and Narrow Street with factors like ·        speed limit, ·        parking, ·        stop at signals etc. After that, a Logical and Mathematical model is creat