Maths for AI
Et Tu Code
Discover the core principles of Mathematics for Artificial Intelligence in our comprehensive ebook In the Introduction to Mathematics in AI understand the pivotal role of math in AI development Gain insights into its applications and the symbiotic relationship between the two fields
1. Introduction to Mathematics in AI Explore why math is crucial for AI development setting the stage for your learning journey
2. Essential Mathematical Concepts Delve into the foundational principles of AI from algebra to core operations essential for navigating the world of AI
3. Statistics for AI Grasp the statistical fundamentals underpinning AI algorithms Learn to interpret data and make informed decisions
4. Optimization in AI Understand optimization techniques to enhance AI performance finetuning algorithms for efficiency
5. Linear Algebra in AI Unlock the power of linear algebra in AI Explore matrices vectors and their applications
6. Calculus for Machine Learning Navigate calculus tailored for machine learning understanding differentiation and integrations role
7. Probability Theory in AI Unravel the mysteries of probability theory in AI applications gaining insights into probabilistic models
8. Advanced Topics in Mathematics for AI Explore advanced mathematical topics elevating your AI understanding
Stay tuned for sections on implementing AI math concepts with Python exploring math behind popular ML algorithms and applications like computer vision and NLP Build a solid math foundation for AI success
Duration - 5h 9m.
Author - Et Tu Code.
Narrator - Helen Green.
Published Date - Saturday, 13 January 2024.
Copyright - © 2024 Et Tu Code ©.
Location:
United States
Description:
Discover the core principles of Mathematics for Artificial Intelligence in our comprehensive ebook In the Introduction to Mathematics in AI understand the pivotal role of math in AI development Gain insights into its applications and the symbiotic relationship between the two fields 1. Introduction to Mathematics in AI Explore why math is crucial for AI development setting the stage for your learning journey 2. Essential Mathematical Concepts Delve into the foundational principles of AI from algebra to core operations essential for navigating the world of AI 3. Statistics for AI Grasp the statistical fundamentals underpinning AI algorithms Learn to interpret data and make informed decisions 4. Optimization in AI Understand optimization techniques to enhance AI performance finetuning algorithms for efficiency 5. Linear Algebra in AI Unlock the power of linear algebra in AI Explore matrices vectors and their applications 6. Calculus for Machine Learning Navigate calculus tailored for machine learning understanding differentiation and integrations role 7. Probability Theory in AI Unravel the mysteries of probability theory in AI applications gaining insights into probabilistic models 8. Advanced Topics in Mathematics for AI Explore advanced mathematical topics elevating your AI understanding Stay tuned for sections on implementing AI math concepts with Python exploring math behind popular ML algorithms and applications like computer vision and NLP Build a solid math foundation for AI success Duration - 5h 9m. Author - Et Tu Code. Narrator - Helen Green. Published Date - Saturday, 13 January 2024. Copyright - © 2024 Et Tu Code ©.
Language:
English
Opening Credits
Duration:00:01:15
2 Preface
Duration:00:02:55
3 Introduction to mathematics in AI
Duration:00:05:43
4 Essential mathematical concepts
Duration:00:05:48
5 Statistics for AI
Duration:00:04:20
6 Optimization in AI
Duration:00:10:14
7 Linear Algebra in AI
Duration:00:04:55
8 Calculus for Machine Learning
Duration:00:04:50
9 Probability theory in AI
Duration:00:05:17
10 Advanced topics in mathematics for ai
Duration:00:06:25
11 Mathematical foundations of neural networks
Duration:00:04:45
12 Mathematics behind popular machine learning algorithms
Duration:00:06:15
13 Mathematics behind popular machine learning algorithms linear regression
Duration:00:03:09
14 mathematics behind popular machine learning algorithms logistic regression
Duration:00:04:12
15 Mathematics behind popular machine learning algorithms decision trees
Duration:00:04:28
16 Mathematics behind popular machine learning algorithms random forests
Duration:00:05:59
17 Mathematics behind popular machine learning algorithms support vector machines (svm)
Duration:00:04:54
18 Mathematics behind popular machine learning algorithms k nearest neighbors (knn)
Duration:00:05:47
19 Mathematics behind popular machine learning algorithms k means clustering
Duration:00:04:38
20 Mathematics behind popular machine learning algorithms principal component analysis (pca)
Duration:00:04:31
21 Mathematics behind popular machine learning algorithms neural networks
Duration:00:06:23
22 Mathematics behind popular machine learning algorithms gradient boosting
Duration:00:05:22
23 Mathematics behind popular machine learning algorithms recurrent neural networks (rnn)
Duration:00:05:10
24 Mathematics behind popular machine learning algorithms long short term memory (lstm)
Duration:00:04:20
25 Mathematics behind popular machine learning algorithms gradient descent
Duration:00:05:46
26 Implementing AI mathematics concepts with python
Duration:00:05:19
27 Implementing AI mathematics concepts with python linear regression implementation
Duration:00:04:23
28 Implementing AI mathematics concepts with python logistic regression implementation
Duration:00:03:44
29 Implementing AI mathematics concepts with python decision trees implementation
Duration:00:04:32
30 Implementing AI mathematics concepts with python random forests implementation
Duration:00:05:12
31 Implementing AI mathematics concepts with python support vector machines (svm) implementation
Duration:00:05:42
32 Implementing AI mathematics concepts with python neural networks implementation
Duration:00:08:28
33 Implementing AI mathematics concepts with python k means clustering implementation
Duration:00:05:29
34 Implementing AI mathematics concepts with python principal component analysis (pca) implementation
Duration:00:05:08
35 Implementing AI mathematics concepts with python gradient descent implementation
Duration:00:05:28
36 Implementing AI mathematics concepts with python recurrent neural networks (rnn) implementation
Duration:00:05:58
37 Implementing AI mathematics concepts with python long short term memory (lstm) implementation
Duration:00:05:40
38 implementing ai mathematics concepts with python gradient boosting implementation
Duration:00:08:48
39 Ppopular python packages for implementing ai mathematics
Duration:00:08:09
40 Popular python packages for implementing ai mathematics numpy
Duration:00:04:03
41 Popular python packages for implementing ai mathematics scipy
Duration:00:05:38
42 Popular python packages for implementing ai mathematics pandas
Duration:00:05:13
43 Popular python packages for implementing ai mathematics sympy
Duration:00:06:00
44 Popular python packages for implementing ai mathematics matplotlib
Duration:00:05:48
45 Popular python packages for implementing ai mathematics seaborn
Duration:00:04:09
46 Popular python packages for implementing ai mathematics scikit learn
Duration:00:06:22
47 Popular python packages for implementing ai mathematics statsmodels
Duration:00:05:20
48 Popular python packages for implementing ai mathematics tensorflow
Duration:00:07:27
49 Popular python packages for implementing ai mathematics pytorch
Duration:00:08:40
50 Applications of mathematics and statistics in ai
Duration:00:07:01
51 Mathematics in computer vision
Duration:00:06:19
52 Mathematics in natural language processing
Duration:00:05:17
53 Mathematics in reinforcement learning
Duration:00:06:08
54 Conclusion: building a strong mathematical foundation for ai
Duration:00:03:50
55 Glossary
Duration:00:05:57
56 Bibliography
Duration:00:05:03
Ending Credits
Duration:00:01:36