The Graphical Model in Machine Learning

The Graphical Model in Machine Learning

Introduction The Graphical model is a subdivision of Machine Learning. It uses a graph to signify a domain problem. A graph states the conditional need structure between random variables. These are being used in many Machine Learning algorithms. For example; Naive Bayes’ algorithm The Hidden Markov Model Restricted Boltzmann machine Neural Networks In this article, … Read more

Gaussian Distribution in Machine Learning

Gaussian Distribution in Machine learning

Introduction The Gaussian distribution is the healthy-studied probability distribution. It is for nonstop-valued random variables. It is as well stated as the normal distribution. Its position makes from the fact that it has many computationally suitable properties. The Gaussian distribution is the backbone of Machine Learning. Every data scientist needs to know during working with … Read more

Text Classification with Naive Bayes classifier

Text Classification with Naive Bayes classifier

Introduction In this post, we are going to discuss that how to classify text using Naive Bayes classifer. Naive Bayes classifiers are collectively a group of classification algorithms. That is based on Bayes’ Theorem. It is not only one algorithm but a family of algorithms. All algorithms mutually share a general principle. For example each … Read more

Natural Language Processing Text Vectorization Approaches

Natural Language Processing Text Vectorization Approaches

Introduction It always needs to transform natural language either text or audio into numerical form for Natural Language Processing to work. Text vectorization approaches are very best choices for traditional machine learning algorithms. They can support converting text to numeric feature vectors. For this purpose, some techniques namely Bag of Words and td-idf vectorization are … Read more

Important Clustering Algorithms in Machine Learning

Important Clustering Algorithms in Machine Learning

Introduction Clustering is a Machine Learning method. It implicates the grouping of data points. It is an unsupervised machine learning task. In which, we draw references from datasets consisting of input data without labelled responses. With a clustering algorithm, we give the algorithm a lot of input data with no labels and let it find … Read more

Polymorphism and Function Overloading in Solidity

Introduction Solidity is an object-oriented programming language that supports contract composition. It means combining many contracts or data types together to make complex data structures and contracts. Solidity also supports inheritance flanked by smart contracts. Inheritance is the process of essential many contracts that are linked to each other over parent-child relationships. In this post, … Read more

Importance of Linear Low Density Polyethylene (LLDPE)

Importance of Linear Low Density Polyethylene

Introduction Importance of Linear Low Density Polyethylene. It is synthetic by copolymerization of ethylene with longer-chain olefins. LLDPE is mass-produced at lower temperatures and pressures. The process of production is used as of copolymerization of ethylene and butene, hexene, or octene. It is very flexible & can be used to make thinner films than HDPE … Read more