Machine Learning for Beginner
- Description
- Curriculum
- FAQ
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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
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What is Machine learning? -
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Understand machine learning concept by the examples we face in daily life
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Machine learning vs Deep learning vs Artificial intelligence vs Data Science
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What are the fields where we can use Machine learning?
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Types of Machine learning
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What are supervised, unsupervised and reinforcement of machine learning?
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Methods for evaluating the machine model
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Types of famous classifiers of Machine learning
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How to develop a Machine model in Python? And what are the steps?
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ebook
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Introduction to Support Vector Machine (SVM)?
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Block diagram of support vector machine. How support vector machine works?
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Linear support vector machine. Understand it graphically
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Optimal Hyperplane of a linear support vector machine. Optimal vs Not optimal
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How linear SVM model predicts? Give a new data and check it graphically
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32
Non-linear support vector machine. Graphs of non-linear SVM models
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33
Kernel technique of non-linear SVM model. Three types of kernel techniques
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34
Transformation from 1-D to 2-D using non-linear kernel trick to separate data
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Transformation from 2-D to 3-D using non-linear kernel trick to separate data
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Applications of support vector machine (SVM) in daily life
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Project: Develop a support vector machine model in Python
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Codes: Colab file and Python file. SVM machine model in Python programming
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ebook
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Introduction to K-Nearest Neighbors classifier (KNN)
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How to KNN machine model works? Understand it graphically
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Concept of KNN machine model with a daily a life example. Check it graphically
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Choosing of an accurate of k value. Why k value is important in KNN model?
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Outliers in KNN model. Why outliers of a data is recommended in KNN model?
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Euclidean distance formula to measure the distance between two data points
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Manhattan distance formula to measure the distance between two data points
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Project: Develop a KNN machine model in Python codes
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Codes: Colab file and Python file. KNN machine model in Python programming
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ebook
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Introduction to Naive Bayes Classifier. What is Bayes rule?
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Understand Naive Bayes rule by giving a daily life example
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Solve an example to cement the concept of Bayes rule
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Project: Develop a Naive Bayes machine model in Python codes
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Codes: Colab file and Python file. Naive Bayes model in Python programming
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ebook
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What is Logistic Regression Classifier? Formula of Logistic regression model
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Understand Logistic Regression machine model graphically
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How to separate a non-linear data by using logistic regression machine model?
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Applications of Logistic Regression machine model in daily life
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Project: Develop a Logistic Regression machine model in Python codes
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Codes:Colab file and Python file.Logistic regression model in Python programming
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ebook
