Scikit-Learn is a library for Python that contains numerous useful algorithms that can easily be implemented and altered for the purpose of classification and other machine learning tasks. One of the most fascinating things about the Scikit-Learn library is that is has a 4-step modelling pattern that makes it easy to code a machine learning classifier: 1.Import the model you want to use: In Scikit-Learn, all machine learning models are implemented as Python classes. 2. Make an instance of the Model. 3. Training the model on the data and storing the information learned from the data. 4. Predicting the labels of new data, using the information the model learned during the training process. IMPLEMENTATION Loading the Dataset: The Scikit-learn library provides numerous datasets, among which we will be using a data set of images called Digits. This data set consists of 1,797 images that are 8x8 pixels in size. Each image is a handwritten digit in grayscale. We load the Dataset as shown...
Recognizing handwritten text is a problem that can be traced back to the first automatic machines that needed to recognize individual characters in handwritten documents. Classifying handwritten text or numbers is important for many real-world scenarios. This article presents recognizing the handwritten digits (0 to 9) using the famous digits data set from Scikit-Learn, using a classifier called Logistic Regression.