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In this article, we will learn about the mathematics behind the SVM classifier, how it classifies the classes, and gives predictions.
Descriptive Statistics is the default process in Data analysis. Here is a quick guide to descriptive statistical analysis.
We will see what actually gradient Descent is and why it became popular and why most of the algorithms in AI and ML follow this technique.
Learn about Cost Functions, Gradient Descent, its Python implementation, types, plotting, learning rates, local minima, and the pros and cons.
Normal Distribution in Statistics and concepts like Histogram, KDE, Skewness, Kurtosis and QQ_Plot are covered in this article.
Are you starting your deep learning career? Here are 5 deep learning essentials you should know while getting started with deep learning.
Game theory 101 can help businesses in decision making using normal form games. Game theory decision making is a helpful way to create strategies.
Learn Mathematics behind machine learning. In this article explore different math aspacts- linear algebra, calculus, probability and much more.
Singular Value Decomposition (SVD) is a common dimensionality reduction technique in data science. Read about the common application of SVD is data science.
Applications of linear algebra in data science and machine learning. These applications of linear algebra will help you to boost your data science skills
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