Basics of Decision Theory – How Medical Diagnosis Apps Work
Watch the video here. In this lesson we would examine the following topics What is Decision Theory Application of Decision ...
What is the Difference Between Machine Learning and Deep Learning?
Hell guys, as you know, I'm Kindson the Genius and good to see you again! In this short lesson, I ...
20 Cool Machine Learning and Data Science Concepts (Simple Definitions)
Hello everyone, as you know, I'm Kindson The Genius. I would like to share with you these 20 cool Machine ...
ML.Net Tutorial 2: Building a Machine Learning Model for Classification
You could also learn Difference Between Machine Learning and Deep Learning. This tutorial follows from Tutorial 1 where you downloaded your dataset, ...
Machine Learning Questions and Answers (Questions 31 to 40)
Welcome back! So we’ll continue with Questions 31 to 40 of our Machine Learning Q&A. You can find Question 1 ...
Machine Learning Questions and Answers (Questions 21 to 30)
Welcome back! So we’ll continue with Questions 21 to 30 of our Machine Learning Q&A. You can find Question 1 ...
Machine Learning Questions and Answers (Questions 11 to 20)
This is Machine Learning Questions and Answer (11 to 20) Find Question 1 to 10 here. So let’s get started! ...
Machine Learning Questions and Answers – (Question 1 to 10)
I’m happy to the making this lesson. I would give you brief answers to several Machine Learning questions. But if ...
What is Likelihood Function in Data Science and Machine Learning?
I will try to explain Likelihood Function in very clear and simple terms. Likelihood Function in Machine Learning and Data ...
Machine Learning 101 – Multiple Linear Regression
You already know of Simple Linear Regression. You also know of Logistic Regression. Now we would discuss Multiple Linear Regression ...
Machine Learning 101 – Minimizing Misclassification Rate in Bayes’ Classifier
In Lecture 4, we learnt about the Bayes’ classifier. Here we would see how to minimize misclassfication rate in Bayes ...
Machine Learning 101 – Basics of Logistic Regression
First I would like clarify that the Logistic Regression model is a model for classification. Also note that Machine Learning ...
Machine Learning 101 – K-Nearest Neighbors Classifier
In the last lecture, we discussed Bayes’ Classifier. Now, we are going to discuss K-Nearest Neighbors Classifier. Remember that Bayes ...
Machine Learning 101 – The Bayes’ Classfier
This is the second lecture on classification. It follow the first one: Introduction to Classification. Bayes’ Classifier is a classifier ...
Machine Learning 101 – Introduction to Classification
In subsequent lectures, we have discussed regression problems. Now we would apply the same analysis to classification but with little ...
Machine Learning 101 – Bias-Variance Trade-off
This Lecture follows from Lecture 7 on Underfitting and Overfitting. Here we would discuss Bias-Variance Trade-off. I will try to ...
Machine Learning 101 – Application of Bayes’ Theorem
In the previous lesson (Lesson 9), we derived Bayes theorem. So let’s write it out: Also recall that Bayes’ theorem ...
Machine Learning 101 – What is Probability Density?
By now, you probably understand probability as well as probability theory. You also know about the Sum Rule and Product ...
Machine Learning 101 – Rules of Probability & Bayes’ Theorem
We will now consider some of the important rules of probability. Meanwhile we would also understand the meaning of terms ...
Machine Learning 101 – Overfitting and Underfitting
Remember that in the previous lecture (Lecture 6), we discuss polynomial curve fitting. We kind of saw that the relationship ...
