AI and ML for Coders
Andrew Hinton
This audiobook is narrated by a digital voice.
Are you ready to unlock the transformative power of Artificial Intelligence (AI) and Machine Learning (ML) in your coding projects? "AI and ML for Coders" is the essential guide for coders who want to leap into the future of technology.
This book is tailored for programmers, developers, and tech enthusiasts eager to integrate AI and ML into their work. Whether you're a seasoned coder or just starting, you'll find invaluable insights and practical knowledge to elevate your craft.
Here's what you'll gain from "AI and ML for Coders":
Authored by a seasoned expert in the field, "AI and ML for Coders" is your roadmap to mastering AI and ML. It's not just a book; it's an investment in your future as a coder in an AI-driven world.
Take advantage of the opportunity to be at the forefront of the AI revolution. Take the next step and add "AI and ML for Coders" to your library today. Your journey into the realm of AI and ML starts here!
Duration - 4h 17m.
Author - Andrew Hinton.
Narrator - Digital Voice Mike G.
Published Date - Monday, 20 January 2025.
Copyright - © 2024 Andrew Hinton ©.
Location:
United States
Networks:
Andrew Hinton
Digital Voice Mike G
AI Fundamentals
Book Bound Studios
English Audiobooks
INAudio Audiobooks
Description:
This audiobook is narrated by a digital voice. Are you ready to unlock the transformative power of Artificial Intelligence (AI) and Machine Learning (ML) in your coding projects? "AI and ML for Coders" is the essential guide for coders who want to leap into the future of technology. This book is tailored for programmers, developers, and tech enthusiasts eager to integrate AI and ML into their work. Whether you're a seasoned coder or just starting, you'll find invaluable insights and practical knowledge to elevate your craft. Here's what you'll gain from "AI and ML for Coders": Authored by a seasoned expert in the field, "AI and ML for Coders" is your roadmap to mastering AI and ML. It's not just a book; it's an investment in your future as a coder in an AI-driven world. Take advantage of the opportunity to be at the forefront of the AI revolution. Take the next step and add "AI and ML for Coders" to your library today. Your journey into the realm of AI and ML starts here! Duration - 4h 17m. Author - Andrew Hinton. Narrator - Digital Voice Mike G. Published Date - Monday, 20 January 2025. Copyright - © 2024 Andrew Hinton ©.
Language:
English
Introduction to Artificial Intelligence and Machine Learning for Coders
Duración:00:16:01
1. Foundations of AI: History, Concepts, and Terminology
Duración:00:02:51
A Brief History of Artificial Intelligence: From Turing to Today
Duración:00:04:17
Core Concepts in AI: Understanding the Building Blocks
Duración:00:03:45
Decoding Machine Learning: Techniques and Applications for Coders
Duración:00:04:00
AI and ML Terminology: Essential Vocabulary for the Modern Coder
Duración:00:03:48
The Future of AI and ML in Coding and Beyond
Duración:00:02:43
Chapter Summary
Duración:00:01:35
2. Machine Learning Basics: Supervised, Unsupervised, and Reinforcement Learning
Duración:00:02:03
Supervised Learning: Training with Labeled Data
Duración:00:03:57
Unsupervised Learning: Discovering Hidden Patterns
Duración:00:04:03
Reinforcement Learning: Learning through Interaction
Duración:00:04:17
Comparing and Choosing the Right Learning Method
Duración:00:03:31
Embracing the Power of AI and ML in Coding
Duración:00:02:10
3. Essential Tools and Libraries for AI and ML Development
Duración:00:02:02
Popular Programming Languages for AI and ML
Duración:00:04:12
Machine Learning Libraries and Frameworks
Duración:00:04:08
Data Visualization and Analysis Tools
Duración:00:03:24
Choosing the Right Tools for Your AI and ML Projects
Duración:00:03:37
4. Data Preparation and Preprocessing Techniques for Machine Learning
Duración:00:02:01
Understanding the Importance of Data Quality in Machine Learning
Duración:00:03:20
Data Cleaning and Handling Missing Values
Duración:00:03:58
Feature Engineering and Selection for Optimal Model Performance
Duración:00:03:24
The Impact of Effective Data Preparation on Machine Learning Success
Duración:00:02:28
5. Supervised Learning Algorithms: Regression, Classification, and Decision Trees
Duración:00:03:20
Exploring Regression Techniques for Predictive Modeling
Duración:00:03:40
Delving into Classification Algorithms for Categorical Data
Duración:00:03:44
Unraveling the Power of Decision Trees in Machine Learning
Duración:00:03:34
Practical Applications and Real-World Examples of Supervised Learning
Duración:00:03:40
Harnessing the Potential of Supervised Learning Algorithms for Coders
Duración:00:02:58
6. Unsupervised Learning Algorithms: Clustering, Dimensionality Reduction, and Association Rules
Duración:00:03:00
Clustering Techniques: K-Means, Hierarchical, and DBSCAN
Duración:00:04:18
Dimensionality Reduction Methods: PCA, t-SNE, and UMAP
Duración:00:03:46
Association Rules: Apriori and Eclat Algorithms
Duración:00:04:14
Practical Applications and Real-World Examples
Duración:00:03:39
Harnessing the Power of Unsupervised Learning Algorithms
Duración:00:02:58
7. Deep Learning and Neural Networks: Architectures, Activation Functions, and Training Techniques
Duración:00:03:13
Exploring Various Neural Network Architectures
Duración:00:04:16
Activation Functions: Types and Applications
Duración:00:04:03
Training Techniques for Optimal Performance
Duración:00:04:06
Real-World Applications of AI and ML in Coding
Duración:00:03:29
The Future of Deep Learning and Neural Networks
Duración:00:03:07
8. Natural Language Processing: Text Analysis, Sentiment Analysis, and Chatbots
Duración:00:02:56
Text Analysis Techniques and Applications
Duración:00:04:00
Sentiment Analysis: Understanding Emotions in Text
Duración:00:03:56
Building Chatbots: Conversational AI and User Interaction
Duración:00:04:45
Integrating AI and ML into Your NLP Projects
Duración:00:04:07
The Future of Natural Language Processing and Its Impact on Coders
Duración:00:03:06
9. Computer Vision and Image Recognition: Convolutional Neural Networks and Object Detection
Duración:00:03:10
Exploring Convolutional Neural Networks: Architecture and Applications
Duración:00:04:33
Object Detection Techniques: From Traditional Methods to Deep Learning Approaches
Duración:00:04:35
Implementing Convolutional Neural Networks for Image Recognition Tasks
Duración:00:04:52
Real-World Applications and Case Studies in Computer Vision
Duración:00:03:40
The Future of Computer Vision and Image Recognition in AI and ML
Duración:00:03:23
10. Ethical Considerations and Responsible AI Development
Duración:00:02:43
Understanding Bias and Fairness in AI and ML Algorithms
Duración:00:04:11
Privacy and Data Security: Safeguarding User Information
Duración:00:03:30
Transparency and Explainability: Building Trust in AI Systems
Duración:00:03:51
Accountability and Regulation: Ensuring Responsible AI Development
Duración:00:03:19
The Future of Ethical AI and ML for Coders
Duración:00:02:32