Tag Archives: machine learning and Data science

Machine Learning Mastery: Gradient Descent algorithm and its variants

Hits: 17 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 …

Machine Learning Mastery: Multiclass classification using scikit-learn

Hits: 155 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 …

Machine Learning Mastery: Types of Learning – Supervised Learning

Hits: 21 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 …

Machine Learning Mastery: Classification vs Regression

Hits: 23 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 …

Machine Learning Mastery: Types of Regression Techniques

Hits: 122 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 …

Machine Learning Mastery: Basic Concept of Classification (Data Mining)

Hits: 30 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 …

Machine Learning Mastery: Getting started with Classification

Hits: 37 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- …

Machine Learning Mastery: Handling Imbalanced Data with SMOTE and Near Miss Algorithm in Python

Hits: 81 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 …

Machine Learning Mastery: One Hot Encoding of datasets in Python

Hits: 311 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 …

Machine Learning Mastery: Label Encoding of datasets in Python

Hits: 16 Label Encoding of datasets in Python   In machine learning, we usually deal with datasets which contains multiple labels in one or more than one columns. These labels can be in the form of words or numbers. To make the data understandable or in human readable form, the training data is often labeled …

Machine Learning Mastery: Feature Scaling – Part 2

Hits: 40 Feature Scaling – Part 2   Feature Scaling is a technique to standardize the independent features present in the data in a fixed range. It is performed during the data pre-processing to handle highly varying magnitudes or values or units. If feature scaling is not done, then a machine learning algorithm tends to …

Machine Learning Mastery: Feature Scaling – Part 1

Hits: 29 Feature Scaling – Part 1   Feature Scaling is a technique to standardize the independent features present in the data in a fixed range. It is performed during the data pre-processing. Working: Given a data-set with features- Age, Salary, BHK Apartment with the data size of 5000 people, each having these independent data features. …

Machine Learning Mastery: Data Cleansing | Introduction

Hits: 25 Data Cleansing | Introduction   Introduction: Data cleaning is one of the important parts of machine learning. It plays a significant part in building a model. Data Cleaning is one of those things that everyone does but no one really talks about. It surely isn’t the fanciest part of machine learning and at …

Machine Learning Mastery: Data Preprocessing for Machine learning in Python

Hits: 51 Data Preprocessing for Machine learning in Python   • Pre-processing refers to the transformations applied to our data before feeding it to the algorithm. • Data Preprocessing is a technique that is used to convert the raw data into a clean data set. In other words, whenever the data is gathered from different …

Machine Learning Mastery: Generate test datasets for Machine learning

Hits: 11 Generate test datasets for Machine learning   Whenever we think of Machine Learning, the first thing that comes to our mind is a dataset. While there are many datasets that you can find on websites such as Kaggle, sometimes it is useful to extract data on your own and generate your own dataset. …