Complete Math, Statistics & Probability for Machine Learning

 Buy Now
  

Price: 199.99$

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 10Cramer’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 ICalculus – Indefinite Integrals IICalculus – Definite Integrals ICalculus – Definite Integrals IICalculus – 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 Linked In 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!