Trang chủ

Business

Business Analytics & Intelligence

Probability

Complete Math, Statistics & Probability for Machine Learning

Loại khoá học: Business Analytics & Intelligence

(Updated 2023) Complete Mathematics, Probability & Statistics for Data Science, Data Analytics, Machine & Deep Learning

50.000 VND

79 VND

Đầy Đủ Bài Giảng

Học Online Tiện Lợi

Kích Hoạt Nhanh 2-5 Phút

Thanh toán tự động

Được phép tải xuống

Mô tả

Start learning Mathematics, Probability & Statistics for Machine Learning TODAY!

Hi,

You are welcome to this course: Complete Math, Probability & Statistics for Machine learning.

This is a highly comprehensive Mathematics, Statistics, and Probability course, you learn everything from Set theory, Combinatorics, Probability, statistics, and linear algebra to Calculus with tons of challenges and solutions for Business Analytics, Data Science, Data Analytics, and Machine Learning. Mathematics, Probability & Statistics are the bedrock of modern science such as machine learning, predictive risk management, inferential statistics, and business decisions. Understanding the depth of these will empower you to solve numerous day-to-day business and scientific prediction problems and analytical problems. This course includes but is not limited to:"

Sets
Universal Set
Proper and Improper Subset
Super Set and Singleton Set
Null or Empty Set
Power Set
Equal and Equivalent Set
Set Builder Notations
Cardinality of Set
Set Operations
Laws of Sets
Finite and Infinite Set
Number Sets
Venn Diagram
Union, Intersection, and Complement of Set
Factorial
Permutations
Combinations
Theoretical Probability
Empirical Probability
Addition Rules of Probability
Mutual and Non-mutual Exclusive
Multiplication Rules of Probability
Dependent and Independent Events
Random Variable
Discrete and Continuous Variable
Z-Score
Frequency and Tally
Population and Sample
Raw Data and Array
Mean
Introduction
Weighted Mean
Properties of Mean
Basic Properties of Mean
Mean Frequency Distribution
Median
Median Frequency Distribution
Mode
Measurement of Spread
Measures of Spread (Variation / Dispersion)
Range
Mean Deviation
Mean Deviation for Frequency Distribution
Variance & Standard Deviation
Understanding Variance and Standard Deviation
Basic Properties of Variance and Standard Deviation
Variable | Dependent- Independent - Moderating - Ordinal...
Variable
Types of Variable
Dependent, Independent, Control Moderating and Mediating Variables
Correlation
Regression & Collinearity
Collinearity
Pearson and Spearman Correlation Methods
Understanding Pearson and Spearman correlation
Spearman Formula
Pearson Formula
Regression Error Metrics
Understanding Regression Error Metrics
Mean Squared Error
Mean Absolute Error
Root Mean Squared Error
R-Squared or Coefficient of Determination
Adjusted R-Squared
Summary on Regression Error Metrics

Conditional Probability
Bayes Theorem
Binomial Distribution
Poisson Distribution
Normal Distribution
Skewness and Kurtisos
T - Distribution
Decision Tree of Probability
Linear Algebra - Matrices
Indices and Logarithms
Introduction to Matrix
Addition and Subtraction - Matrices
Multiplication - Matrice
Square of Matrix
Transpose of Matrix
Special Matrix
Determinant of Matrix
Determinant of Singular Matrix - Example
Cofactor
Minor
Place Sign
Adjoint of a Square Matrix
Inverse of Matrix
The inverse of Matrix - Example
Matrix for Simultaneous Equation - Exercise & Solution 10
Cramer's Rule
Cramer's Rule Example
Eigenvalues and Eigenvectors
Euclidean Distance and Manhattan Distance
Differentiation
Importance of Calculus for Machine Learning
The gradient of a Straight Line
The gradient of a Curve to Understanding Differentiation
Derivatives By First Principle
Derived Definition Form of First Principle
General Formula
Second Derivatives
Understanding Second Derivatives
Special Derivatives
Understanding Special Derivatives
Differentiation Using Chain Rule
Understanding Chain Rule
Differentiation Using Product Rule
Understanding Product Rule
Differentiation Using Chain and Product Rules
Calculus - Indefinite Integrals I
Calculus - Indefinite Integrals II
Calculus - Definite Integrals I
Calculus - Definite Integrals II
Calculus - Area Under Curve - Using Integration

You will also have access to the Q&A section where you contact post questions. You can also send me a direct message.

Upon the completion of this course, you’ll receive a certificate of completion which you can post on your LinkedIn account for our colleagues and potential employers to view! All these come with a 30-day money-back guarantee. so you can try out the course risk-free!

Who is this course for:

Those starting from scratch in Machine Learning
Those who wish to take their career to the next level
Professional in the field of Data Science
Professionals in the banking industry
Professionals in the insurance industry

Master the core Mathematics, Probability & Statistics for Business Analytics, Data Science, AI, Machine & Deep Learning!

Bạn sẽ học được gì

Learn Linear Algebra, Calculus for Machine and Deep Learning

Learn to use Python to Solve Maths Problems

Learn Discrete Maths for Machine and Deep Learning

Learn Probability theory for Machine and Deep Learning

Different types of distributions: Normal, Binomial, Poisson...

Learn set theory, permutation and combination in details

Understand how to link probability with statistics

You will learn how to apply Bayes' theorem

You will learn mutually and non-mutually exclusive laws of probability

You will learn dependent and independent events of probaility

A lot more...

Yêu cầu

Basic maths

Nội dung khoá học

79 sections

Set Theory

97 lectures

ML Success Starts Here: Master Math, Probability & Statistics for ML!