Skip to main content

About Author

Image
By

           Dr. Angajala Srinivasa Rao

B.Sc., M.E(GeoInf), M.Tech(CSE), M.Tech(Comm), 
M.Tech(CSE), M.Tech(Comm), M.S(Ukraine), Ph.D

MIEEE, LMCSI, LMISTE, MIACSIT, MCSTA, IAENG


I am currently employed as a professor at a prestigious engineering college in Andhra Pradesh, India. With over 26 years of experience in the education field, I am well-versed in training, research, and teaching. My educational career began at the age of three, and my ambition is to gain a minimum knowledge of technology by the end of my life, if not sooner. With a strong interest in technology, I began my new technical job career with highly professional technocrats in the third act of my life.


With the rapid growth of technology, I want to share my feelings and views about new technologies and hear from you. I'm thirsty and eager to become aware of recent technology trends. "Writing content, learning notes and creating websites about new technologies Artificial Intelligence, data science, machine learning, deep learning, cloud computing, edge computing, quantum computing, robotics and automation, 5G communication technology, blockchain technologies, full-stack development, virtual and augmented reality and etc., in depth towards to research.

Comments

Post a Comment

Popular posts from this blog

What is Machine Learning

By
Definition of  Machine Learning and Introduction Concepts of Machine Learning Introduction What is machine learning ? History of Machine Learning Benefits of Machine Learning Advantages of Machine Learning Disadvantages of Machine Learning   Machine Learning  Applications Well-posed learning problem Designing a learning system Perspectives and issues in machine learning  Applications of Machine Learning Machine Learning Lifecycle Types of Machine Learning What is Machine Learning? Well-posed learning problem Designing a learning system Perspectives and issues in machine learning  Applications of Machine Learning Machine Learning Lifecycle Types of Machine Learning What is machine learning?  Machine learning (ML) is a subfield of artificial intelligence (AI) that focuses on creating algorithms that can learn from and make predictions or decisions based on data. It is a rapidly growing field that has transformed various industries and has the potential to rev...
Post a Comment
Read more

Know the Machine Learning Syllabus

By
Learn Machine Learning Step-by-step INDEX  1. Introduction to Machine Learning What is Machine Learning? Applications of Machine Learning Machine Learning Lifecycle Types of Machine Learning   2. Exploratory Data Analysis Data Cleaning and Preprocessing Data Visualization Techniques Feature Extraction and Feature Selection  
Post a Comment
Read more

What is Bayes Theorem

By
Bayesian Theorem and Concept Learning  Bayesian learning Topics Introduction Bayes theorem Concept learning Maximum Likelihood and least squared error hypotheses Maximum likelihood hypotheses for predicting probabilities Minimum description length principle, Bayes optimal classifier, Gibs algorithm, Naïve Bayes classifier, an example: learning to classify text,  Bayesian belief networks, the EM algorithm. What is Bayesian Learning? Bayesian learning is a type of machine learning that uses Bayesian probability theory to make predictions and decisions based on data.
Post a Comment
Read more

What is Analytical Machine Learning

By
Analytical  and  Explanation-based learning  with domain theories  Analytical Learning Concepts Introduction Learning with perfect domain theories: PROLOG-EBG Explanation-based learning Explanation-based learning of search control knowledge Analytical Learning Definition :  Analytical learning is a type of machine learning that uses statistical and mathematical techniques to analyze and make predictions based on data.
Post a Comment
Read more

Machine Learning Sets of Rules

By
Sequential Covering Algorithms and  Learning sets of First-Order rules:  Set of Rules :  Learning a set of rules is a type of machine learning that focuses on discovering patterns or rules that explain the data.  Introduction Sequential covering algorithms Learning First-Order rules Learning sets of First-Order rules: FOIL Summary Introduction  Learning sets of rules is a type of machine learning that involves learning a set of rules from data that can be used to make predictions or classifications. One popular approach to learning sets of rules is through the use of sequential covering algorithms.
Post a Comment
Read more

Total Pageviews

Followers