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Machine Learning for Beginner

 

Machine Learning for Beginner


Machine Learning for Beginner

Learn Machine Learning from scratch. Theoretical & Graphical explanation of classifiers with projects in Python

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0.0  (0 ratings)

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Created by Moein Ud Din

Published

English


What you'll learn

  1. Fundamental of Machine Learning; Introduction, types of machine learning, applications
  2. Supervised, Unsupervised and Reinforcement learning
  3. Principal Component Analysis (PCA); Introduction, mathematical and graphical concepts
  4. Confusion matrix, Under-fitting and Over-fitting, classification and regression of machine model
  5. Support Vector Machine (SVM) Classifier; Introduction, linear and non-linear SVM model, optimal hyperplane, kernel trick, project in Python
  6. K-Nearest Neighbors (KNN) Classifier; Introduction, k-value, Euclidean and Manhattan distances, outliers, project in Python
  7. Naive Bayes Classifier; Introduction, Bayes rule, project in Python
  8. Logistic Regression Classifier; Introduction, non-linear logistic regression, sigmoid function, project in Python
  9. Decision Tree Classifier; Introduction, project in Python


Course content

10 sections • 67 lectures • 6h 51m total length


Requirements

Basics of Python


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Description

Learn Machine Learning from scratch, this course for beginner who want to learn the fundamental of machine learning and artificial intelligence. the course includes video explanation with introductions(basics), detailed theory and graphical explanations. Some daily life projects have been solved by using Python programming. Downloadable files of ebooks and Python codes have been attached to all the sections. The lectures are appealing, fancy and fast. They take less time to walk you through the whole content. Each and every topic has been taught extensively in depth to cover all the possible areas to understand the concept in most possible easy way. It's highly recommended for the students who don’t know the fundamental of machine learning studying at college and university level.


The objective of this course is to explain the Machine learning and artificial intelligence in a very simple and way to understand. I strive for simplicity and accuracy with every definition, code I publish. All the codes have been conducted through colab which is an online editor. Python remains a popular choice among numerous companies and organization. Python has a reputation as a beginner-friendly language, replacing Java as the most widely used introductory language because it handles much of the complexity for the user, allowing beginners to focus on fully grasping programming concepts rather than minute details.


Below is the list of topics that have been covered:


Introduction to Machine Learning


Supervised, Unsupervised and Reinforcement learning


Types of machine learning


Principal Component Analysis (PCA)


Confusion matrix


Under-fitting & Over-fitting


Classification


Linear Regression


Non-linear Regression


Support Vector Machine Classifier


Linear SVM machine model


Non-linear SVM machine model


Kernel technique


Project of SVM in Python


K-Nearest Neighbors (KNN) Classifier


k-value in KNN machine model


Euclidean distance


Manhattan distance


Outliers of KNN machine model


Project of KNN machine model in Python


Naive Bayes Classifier


Byes rule


Project of Naive Bayes machine model in Python


Logistic Regression Classifier


Non-linear logistic regression


Project of Logistic Regression machine model in Python


Decision Tree Classifier


Project of Decision Tree machine model in Python


Who this course is for:

Beginners of Machine learning developers curious about machine model



Instructor : Moein Ud Din

Engineer

Moein Ud Din

4.6 Instructor Rating

150 Reviews

30,049 Students

5 Courses

This is Moein Ud Din, I am instructor of mathematics, a programmer of Python, Artificial intelligence, machine learning, deep learning, image processing, NLP  and  an animation geek. It's my passion to pass my knowledge what I know to the desired entities. Kinda quintessential person, always hounding to make things ideal. I have plan in future to prepare more mathematics and IT courses, would love to make things change in my own certain way. Critics are most welcome as long as it helps me and my students. Best wishes 




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