Fundamentals of Machine Learning
DSA Shots
Welcome to "Fundamentals of Machine Learning"! This comprehensive guide is designed to provide an introduction to the fascinating world of machine learning and artificial intelligence. Whether you're a seasoned programmer or just starting out, this book will take you on a journey through the fundamentals of these technologies and their applications in various industries.
Artificial Intelligence (AI) has been a buzzword for years, but what does it really mean? In simple terms, AI refers to any software that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Machine learning is a subset of AI that focuses on developing algorithms and statistical models that enable computers to learn from data without being explicitly programmed.
This book will cover the following topics:
* Introduction to Artificial Intelligence and Machine Learning
* Differences Between Classical Programming and Artificial Intelligence
* Machine Learning Models and their Types (Supervised, Unsupervised, and Reinforcement Learning)
* Deep Learning Techniques and Large Language Models (LLMs)
* Applications of Machine Learning in various industries such as Healthcare, Finance, Marketing, and more.
By the end of this book, you will have a solid understanding of the fundamentals of machine learning and artificial intelligence, and how they can be applied to real-world scenarios. Whether you're looking to start a career in this field or simply want to learn more about it, this book is an excellent starting point for your journey. So, let's get started!
Duration - 3h 32m.
Author - DSA Shots.
Narrator - H. Green.
Published Date - Monday, 08 January 2024.
Copyright - © 2023 DSA Shots ©.
Location:
United States
Description:
Welcome to "Fundamentals of Machine Learning"! This comprehensive guide is designed to provide an introduction to the fascinating world of machine learning and artificial intelligence. Whether you're a seasoned programmer or just starting out, this book will take you on a journey through the fundamentals of these technologies and their applications in various industries. Artificial Intelligence (AI) has been a buzzword for years, but what does it really mean? In simple terms, AI refers to any software that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Machine learning is a subset of AI that focuses on developing algorithms and statistical models that enable computers to learn from data without being explicitly programmed. This book will cover the following topics: * Introduction to Artificial Intelligence and Machine Learning * Differences Between Classical Programming and Artificial Intelligence * Machine Learning Models and their Types (Supervised, Unsupervised, and Reinforcement Learning) * Deep Learning Techniques and Large Language Models (LLMs) * Applications of Machine Learning in various industries such as Healthcare, Finance, Marketing, and more. By the end of this book, you will have a solid understanding of the fundamentals of machine learning and artificial intelligence, and how they can be applied to real-world scenarios. Whether you're looking to start a career in this field or simply want to learn more about it, this book is an excellent starting point for your journey. So, let's get started! Duration - 3h 32m. Author - DSA Shots. Narrator - H. Green. Published Date - Monday, 08 January 2024. Copyright - © 2023 DSA Shots ©.
Language:
English
1 Opening Credits
Duration:00:01:21
2 Preface
Duration:00:02:11
3 Introduction
Duration:00:02:06
4 artificial intelligence
Duration:00:06:11
5 differences between classical programming and artificial intelligence
Duration:00:04:57
6 machine learning
Duration:00:04:19
7 deep learning
Duration:00:04:35
8 applied vs generalized ai
Duration:00:07:09
9 machine learning features and labels
Duration:00:03:33
10 machine learning training models
Duration:00:05:05
11 machine learning training models types of training models
Duration:00:05:06
12 machine learning training models hyperparameter tuning
Duration:00:05:03
13 machine learning supervised learning
Duration:00:06:52
14 machine learning supervised learning regression
Duration:00:05:44
15 machine learning supervised learning classification
Duration:00:04:14
16 machine learning supervised learning applications of supervised learning
Duration:00:04:45
17 machine learning classification
Duration:00:04:34
18 machine learning regression
Duration:00:05:20
19 machine learning unsupervised learning
Duration:00:03:53
20 machine learning unsupervised learning clustering
Duration:00:04:43
21 machine learning unsupervised learning dimension reduction
Duration:00:03:49
22 machine learning unsupervised learning applications of unsupervised learning
Duration:00:04:28
23 reinforcement learning
Duration:00:05:43
24 reinforcement learning applications of reinforcement learning
Duration:00:04:15
25 generative ai
Duration:00:06:17
26 generative ai generative ai algorithms
Duration:00:04:19
27 large language models (llms)
Duration:00:05:03
28 large language models (llms) popular llms
Duration:00:04:48
29 large language models (llms) applications of llms
Duration:00:05:06
30 openai
Duration:00:04:40
31 openai popular openai products
Duration:00:03:30
32 openai chatgpt
Duration:00:05:00
33 openai openai models
Duration:00:04:27
34 llama 2 meta ai
Duration:00:04:04
35 llama 2 meta ai popular meta ai products
Duration:00:04:26
36 llama 2 meta ai llama 2 meta ai models
Duration:00:03:16
37 hugging face ai community
Duration:00:03:17
38 hugging face ai community popular hugging face ai products
Duration:00:04:40
39 hugging face ai community hugging face ai popular models
Duration:00:05:13
40 langchain framework
Duration:00:02:33
41 langchain framework langchain framework features
Duration:00:06:07
42 langchain framework langchain use cases
Duration:00:04:59
43 Appendix
Duration:00:03:40
44 Bibliography
Duration:00:06:31
45 Glossary
Duration:00:03:09
46 Acknowledgment
Duration:00:05:39
47 Ending Credits
Duration:00:02:09