Mathematics For Ai & Ml Developers The Complete Course

What you'll learn
Learn the fundamental Mathematics required for machine learning development
Learn core concepts of probability theory
Learn all about calculus and its application in AI & ML
Learn lineal algebra and neural networks
Requirements
Basic knowledge of mathematics is required to complete this course
Description
Mathematics for AIIf you want to develop AI solutions, you need to know the key formulas and computational theories and the mathematical algorithms used to analyze the data and statistics.So, Want To Know How Maths Plays A Key Role In Developing AI Solutions?This program is designed for the one who wants to become a complete AI specialist by gaining mastery over mathematical algorithms of AI. This course will help you learn the most important theories of probability, algebra, and calculus for data science and artificial intelligence.This course will help you learn how probability stimulates probabilistic models using python. You'll learn about probability mathematical frameworks which allow analyzing the chances of events in a logical manner. Also, this course gives you in-depth knowledge on how to deal with uncertainty in AI. This course provides you with knowledge of calculus that helps you understand the hidden pieces in the AI patterns.Basically, you are going to get every single knowledge regarding mathematics in AI through this program.Major Concepts That You'll LearnIntroduction to Mathematics for AIProbability theoryIntroduction to Calculus and DerivativesCalculus Continued and IntegralsIntroduction to Linear AlgebraLinear Algebra ContinuedNeural Networks from ScratchThis course also covers essential topics like linear algebra and neural networks which help you develop reliable AI models.Perks Of Availing This Program!Get Well-Structured ContentLearn From Industry ExpertsIncludes The Must-Learn AI Mathematical ConceptsSo why are you waiting? make your move to become an AI specialist now.See You In The Class!
Overview
Section 1: Introduction to Mathematics for AI
Lecture 1 Course Introduction
Section 2: Probability theory
Lecture 2 Section Overview
Lecture 3 Introduction to Probabilty theory
Lecture 4 Combinatorics
Lecture 5 Multiple events
Lecture 6 Section Summary
Section 3: Introduction to Calculus and Derivatives
Lecture 7 Section Overview
Lecture 8 The Essence of Calculus, Integrals and Derivatives
Lecture 9 Limits
Lecture 10 Derivative Formulas and Geometric Intuition
Lecture 11 Derivation Rules: Power Rule, Product Rule and Chain Rule
Lecture 12 Euler's Number and Continuous Growth
Lecture 13 Implicit differentiation
Lecture 14 Section Summary
Section 4: Calculus Continued and Integrals
Lecture 15 Section Overview
Lecture 16 Integral Intuition
Lecture 17 Integral Intuition Continued
Lecture 18 Indefinite Integrals
Lecture 19 Definite Integrals
Lecture 20 Integration in Python
Lecture 21 Calculus in Machine Learning
Lecture 22 Section Summary
Section 5: Introduction to Linear Algebra
Lecture 23 Section Overview
Lecture 0 Linear Algebra Intuition
Lecture 0 Linear Transformations
Lecture 0 Introduction to Matrices
Lecture 0 Matrices Continued
Lecture 0 Dot Product
Lecture 0 Matrix Patterns
Lecture 24 Section Summary
Section 6: Linear Algebra Continued
Lecture 25 Section Overview
Lecture 0 Determinant
Lecture 0 Cross Products
Lecture 0 Vector Calculus
Lecture 0 Change of Basis
Lecture 0 EigenVectors and EigenValues
Lecture 0 EigenVectors and EigenValues continued
Lecture 26 Section Summary
Section 7: Neural Networks from Scratch
Lecture 0 Section Overview
Lecture 0 Neural Networks
Lecture 0 Creating Model Classes
Lecture 0 Model Training
Lecture 0 Summary
Anyone who wants to learn the important mathematical concepts required for AI & ML will find this course very useful


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