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    100% Discount || Machine Learning for Beginner

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    Machine Learning for Beginner

    Requirements

    • Basics of Python

    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:

    1. Introduction to Machine Learning
    2. Supervised, Unsupervised and Reinforcement learning
    3. Types of machine learning
    4. Principal Component Analysis (PCA)
    5. Confusion matrix
    6. Under-fitting & Over-fitting
    7. Classification
    8. Linear Regression
    9. Non-linear Regression
    10. Support Vector Machine Classifier
    11. Linear SVM machine model
    12. Non-linear SVM machine model
    13. Kernel technique
    14. Project of SVM in Python
    15. K-Nearest Neighbors (KNN) Classifier
    16. k-value in KNN machine model
    17. Euclidean distance
    18. Manhattan distance
    19. Outliers of KNN machine model
    20. Project of KNN machine model in Python
    21. Naive Bayes Classifier
    22. Byes rule
    23. Project of Naive Bayes machine model in Python
    24. Logistic Regression Classifier
    25. Non-linear logistic regression
    26. Project of Logistic Regression machine model in Python
    27. Decision Tree Classifier
    28. Project of Decision Tree machine model in Python

    Who this course is for:

    • Beginners of Machine learning developers curious about machine model


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