Machine learning
Et Tu Code
Dive into the fascinating realm of artificial intelligence with 'Machine Learning: Demystifying the World of Intelligent Systems'. This comprehensive guide offers a clear and concise journey through the intricate landscape of machine learning. From its historical roots in the 1950s to cutting-edge advancements, the book covers everything from fundamental concepts to advanced techniques.
Explore the core pillars of machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning. Understand how machines learn from labeled and unlabeled data, model complex relationships, and make decisions to maximize rewards.
Discover the critical role of feature engineering and evaluation metrics in crafting high-performing models. Learn about the ethical considerations surrounding AI technologies and their real-world applications across diverse industries, from healthcare to finance.
Whether you're a novice eager to grasp the basics or a seasoned practitioner seeking to stay abreast of recent advances, this book equips you with the knowledge and tools essential to navigate the ever-evolving landscape of machine learning. With insights into popular algorithms, tools, and libraries, as well as discussions on recent trends like transfer learning and generative models, 'Machine Learning' is your indispensable companion in unraveling the mysteries of intelligent systems.
Duration - 21h 12m.
Author - Et Tu Code.
Narrator - Helen Green.
Published Date - Wednesday, 03 January 2024.
Copyright - © 2023 Et Tu Code ©.
Location:
United States
Description:
Dive into the fascinating realm of artificial intelligence with 'Machine Learning: Demystifying the World of Intelligent Systems'. This comprehensive guide offers a clear and concise journey through the intricate landscape of machine learning. From its historical roots in the 1950s to cutting-edge advancements, the book covers everything from fundamental concepts to advanced techniques. Explore the core pillars of machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning. Understand how machines learn from labeled and unlabeled data, model complex relationships, and make decisions to maximize rewards. Discover the critical role of feature engineering and evaluation metrics in crafting high-performing models. Learn about the ethical considerations surrounding AI technologies and their real-world applications across diverse industries, from healthcare to finance. Whether you're a novice eager to grasp the basics or a seasoned practitioner seeking to stay abreast of recent advances, this book equips you with the knowledge and tools essential to navigate the ever-evolving landscape of machine learning. With insights into popular algorithms, tools, and libraries, as well as discussions on recent trends like transfer learning and generative models, 'Machine Learning' is your indispensable companion in unraveling the mysteries of intelligent systems. Duration - 21h 12m. Author - Et Tu Code. Narrator - Helen Green. Published Date - Wednesday, 03 January 2024. Copyright - © 2023 Et Tu Code ©.
Language:
English
Opening Credits
Duration:01:24:19
2 Preface
Duration:02:14:57
3 Introduction to machine learning
Duration:07:03:16
4 History of machine learning
Duration:06:40:14
5 History of machine learning early concepts and foundations
Duration:06:14:26
6 History of machine learning the emergence of artificial intelligence
Duration:05:12:14
7 History of machine learning statistical approaches
Duration:05:03:26
8 History of machine learning connectionism and neural networks
Duration:05:08:07
9 history of machine learning machine learning boom in the 20th century
Duration:04:16:38
10 history of machine learning rise of big data and computational power
Duration:05:56:31
11 history of machine learning deep learning revolution
Duration:04:30:12
12 supervised learning
Duration:04:54:16
13 unsupervised learning
Duration:05:03:14
14 deep learning
Duration:06:51:33
15 feature engineering
Duration:05:16:00
16 evaluation metrics
Duration:03:57:48
17 model deployment
Duration:03:54:33
18 reinforcement learning
Duration:05:16:45
19 popular machine learning algorithms
Duration:04:40:09
20 popular machine learning algorithms linear regression
Duration:06:31:57
21 popular machine learning algorithms logistic regression
Duration:05:34:45
22 popular machine learning algorithms decision trees
Duration:04:33:45
23 popular machine learning algorithms random forest
Duration:06:55:50
24 popular machine learning algorithms support vector machines (svm)
Duration:04:04:09
25 popular machine learning algorithms k nearest neighbors (knn)
Duration:06:32:40
26 popular machine learning algorithms k means clustering
Duration:05:01:45
27 popular machine learning algorithms neural networks
Duration:04:26:57
28 popular machine learning algorithms gradient boosting
Duration:06:35:40
29 popular machine learning algorithms principal component analysis (pca)
Duration:06:17:45
30 popular machine learning algorithms recurrent neural networks (rnn)
Duration:05:58:02
31 popular machine learning algorithms natural language processing (nlp) algorithms
Duration:05:16:55
32 popular tools and libraries in machine learning
Duration:05:03:12
33 popular tools and libraries in machine learning numpy
Duration:05:16:14
34 popular tools and libraries in machine learning pandas
Duration:04:44:24
35 popular tools and libraries in machine learning scikit learn
Duration:05:51:50
36 popular tools and libraries in machine learning tensorflow
Duration:04:39:02
37 popular tools and libraries in machine learning pytorch
Duration:03:48:12
38 popular tools and libraries in machine learning keras
Duration:05:34:09
39 popular tools and libraries in machine learning jupyter notebooks
Duration:04:52:02
40 popular tools and libraries in machine learning matplotlib and seaborn
Duration:04:18:31
41 popular tools and libraries in machine learning scipy
Duration:04:35:00
42 popular tools and libraries in machine learning xgboost
Duration:05:08:45
43 ethical considerations in machine learning
Duration:03:34:07
44 machine learning in real world applications
Duration:04:24:43
45 recent advances and trends
Duration:05:38:57
46 Glossary
Duration:04:24:14
47 Bibliography
Duration:04:39:28
Ending Credits
Duration:01:52:12