{"id":1547,"date":"2020-08-22T22:15:15","date_gmt":"2020-08-22T20:15:15","guid":{"rendered":"https:\/\/kindsonthegenius.com\/blog\/?page_id=1547"},"modified":"2020-08-22T22:15:52","modified_gmt":"2020-08-22T20:15:52","slug":"ai-machine-learning-and-data-science-tutorials","status":"publish","type":"page","link":"https:\/\/kindsonthegenius.com\/blog\/ai-machine-learning-and-data-science-tutorials\/","title":{"rendered":"AI, Machine Learning and Data Science Tutorials"},"content":{"rendered":"

Basics of Decision Theory – How Medical Diagnosis Apps Work<\/a><\/h4>\n
Watch the video here. In this lesson we would examine the following topics What is Decision Theory Application of Decision ...
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What is the Difference Between Machine Learning and Deep Learning?<\/a><\/h4>\n
Hell guys, as you know, I'm Kindson the Genius and good to see you again! In this short lesson, I ...
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20 Cool Machine Learning and Data Science Concepts (Simple Definitions)<\/a><\/h4>\n
Hello everyone, as you know, I'm Kindson The Genius. I would like to share with you these 20 cool Machine ...
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ML.Net Tutorial 2: Building a Machine Learning Model for Classification<\/a><\/h4>\n
You could also learn Difference Between Machine Learning and Deep Learning.\u00a0This tutorial follows from\u00a0Tutorial 1\u00a0 where you downloaded your dataset, ...
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Machine Learning Questions and Answers (Questions 31 to 40)<\/a><\/h4>\n
Welcome back! So we’ll continue with Questions 31 to 40 of our Machine Learning Q&A. You can find Question 1 ...
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Machine Learning Questions and Answers (Questions 21 to 30)<\/a><\/h4>\n
Welcome back! So we’ll continue with Questions 21 to 30 of our Machine Learning Q&A. You can find Question 1 ...
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Machine Learning Questions and Answers (Questions 11 to 20)<\/a><\/h4>\n
This is Machine Learning Questions and Answer (11 to 20) Find Question 1 to 10 here. So let’s get started! ...
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Machine Learning Questions and Answers \u2013 (Question 1 to 10)<\/a><\/h4>\n
I’m happy to the making this lesson. I would give you brief answers to several Machine Learning questions. But if ...
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What is Likelihood Function in Data Science and Machine Learning?<\/a><\/h4>\n
I will try to explain Likelihood Function in very clear and simple terms. Likelihood Function in Machine Learning and Data ...
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Machine Learning 101 \u2013 Multiple Linear Regression<\/a><\/h4>\n
You already know of Simple Linear Regression. You also know of Logistic Regression. Now we would discuss Multiple Linear Regression ...
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Machine Learning 101 \u2013 Minimizing Misclassification Rate in Bayes\u2019 Classifier<\/a><\/h4>\n
In Lecture 4, we learnt about the Bayes’ classifier. Here\u00a0 we would see how to minimize misclassfication rate in Bayes ...
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Machine Learning 101 \u2013 Basics of Logistic Regression<\/a><\/h4>\n
First I would like clarify that the Logistic Regression model is a model for classification. Also note that Machine Learning ...
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Machine Learning 101 \u2013 K-Nearest Neighbors Classifier<\/a><\/h4>\n
In the last lecture, we discussed Bayes’ Classifier. Now, we are going to discuss K-Nearest Neighbors Classifier. Remember that Bayes ...
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Machine Learning 101 \u2013 The Bayes\u2019 Classfier<\/a><\/h4>\n
This is the second lecture on classification. It follow the first one: Introduction to Classification. Bayes’ Classifier is a classifier ...
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Machine Learning 101 \u2013 Bias-Variance Trade-off<\/a><\/h4>\n
This Lecture follows from Lecture 7 on Underfitting and Overfitting. Here we would discuss Bias-Variance Trade-off. I will try to ...
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Machine Learning 101 \u2013 Introduction to Classification<\/a><\/h4>\n
In subsequent lectures, we have\u00a0 discussed regression problems. Now we would apply the same analysis to classification but with little ...
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Machine Learning 101 \u2013 Application of Bayes\u2019 Theorem<\/a><\/h4>\n
In the previous lesson (Lesson 9), we derived Bayes theorem. So let’s write it out: Also recall that Bayes’ theorem ...
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Machine Learning 101 \u2013 What is Probability Density?<\/a><\/h4>\n
By now, you probably understand probability as well as probability theory. You also know about the Sum Rule and Product ...
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Machine Learning 101 \u2013 Rules of Probability & Bayes\u2019 Theorem<\/a><\/h4>\n
We will now consider some of the important rules of probability. Meanwhile we would also understand the meaning of terms ...
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Machine Learning 101 \u2013 Overfitting and Underfitting<\/a><\/h4>\n
Remember that in the previous lecture (Lecture 6), we\u00a0 discuss polynomial curve fitting. We kind of saw that the relationship ...
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