Stochastic Gradient Descent (SGD) What is Gradient Descent? Before explaining Stochastic Gradient Descent (SGD), let’s first describe what Gradient Descent is. Gradient Descent is a popular optimization technique in Machine Learning and Deep Learning, and it can be used with most, if not all, of the learning algorithms. A gradient is the slope of …
Gradient Descent algorithm and its variants Gradient Descent is an optimization algorithm used for minimizing the cost function in various machine learning algorithms. It is basically used for updating the parameters of the learning model. Types of gradient Descent: Batch Gradient Descent: This is a type of gradient descent which processes all the training …
Multiclass classification using scikit-learn Multiclass classification is a popular problem in supervised machine learning. Problem – Given a dataset of m training examples, each of which contains information in the form of various features and a label. Each label corresponds to a class, to which the training example belongs to. In multiclass classification, we have a finite …
Types of Learning – Supervised Learning What is Learning for a machine? A machine is said to be learning from past Experiences(data feed in) with respect to some class of Tasks, if it’s Performance in a given Task improves with the Experience.For example, assume that a machine has to predict whether a customer will buy a specific product lets …
Classification vs Regression Classification and Regression are two major prediction problems which are usually dealt with Data mining and machine learning. Classification is the process of finding or discovering a model or function which helps in separating the data into multiple categorical classes i.e. discrete values. In classification, data is categorized under different labels according …
Types of Regression Techniques When Regression is chosen? A regression problem is when the output variable is a real or continuous value, such as “salary” or “weight”. Many different models can be used, the simplest is the linear regression. It tries to fit data with the best hyperplane which goes through the points. Regression …
Basic Concept of Classification (Data Mining) Data Mining: Data mining in general terms means mining or digging deep into data which is in different forms to gain patterns, and to gain knowledge on that pattern. In the process of data mining, large data sets are first sorted, then patterns are identified and relationships are …
Getting started with Classification Introduction As the name suggests, Classification is the task of “classifying things” into sub-categories.But, by a machine! If that doesn’t sound like much, imagine your computer being able to differentiate between you and a stranger. Between a potato and a tomato. Between an A grade and a F- . Yeah. …
Handling Imbalanced Data with SMOTE and Near Miss Algorithm in Python In Machine Learning and Data Science we often come across a term called Imbalanced Data Distribution, generally happens when observations in one of the class are much higher or lower than the other classes. As Machine Learning algorithms tend to increase accuracy by reducing …
One Hot Encoding of datasets in Python Sometimes in datasets, we encounter columns that contain numbers of no specific order of preference. The data in the column usually denotes a category or value of the category and also when the data in the column is label encoded. This confuses the machine learning model, to …