Calculus -for Generative AI ,Data Science & Machine Learning

Overview

Unlock the Power of Calculus in Machine Learning, Deep Learning, Data Science, and AI with Python:

A Comprehensive Guide to Mastering Essential Mathematical Skills"

Syllabus

• Introduction to Calculus for AI
Overview of Calculus' Role in AI and Machine Learning
Course Objectives and Structure
Introduction to Python for Calculus
• Fundamental Concepts of Calculus
Limits and Continuity
Derivatives
Integrals
The Fundamental Theorem of Calculus
• Calculus in Machine Learning
Gradient Descent and its Mathematical Foundations
Optimization Techniques Using Calculus
Understanding Loss Functions and Their Derivatives
• Multivariable Calculus
Partial Derivatives and Their Applications
Gradients and Hessians
Optimization in Higher Dimensions
• Calculus in Deep Learning
Backpropagation and Chain Rule
Calculus of Neural Networks
Practical Applications: Accelerating Training with Calculus
• Calculus for Data Science
Calculus in Data Preprocessing and Feature Engineering
Analyzing Data Trends Using Derivatives
Calculus-based Stochastic Processes
• Differential Equations in AI
Introduction to Differential Equations
Solving Differential Equations with Python
Applications in Predictive Modeling
• Advanced Topics
Calculus of Variations and Regularization Techniques
Laplace Transforms in Signal Processing
Fourier Analysis for Data Science
• Practical Applications and Projects
Calculus in Reinforcement Learning
Exploratory Data Analysis with Calculus
Real-world Projects Integrating Calculus with AI
• Tools and Python Libraries
Introduction to SymPy for Symbolic Calculus
Using NumPy and SciPy for Computational Calculus
Visualization with Matplotlib and Seaborn
• Review and Future Directions
Key Takeaways and Summary of main concepts
Emerging Trends in AI Using Calculus
Resources for Further Learning and Exploration

Taught by

Manifold AI Learning ®

Subjects

Data Science