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
Findaway 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
Duration:00:16:01
1. Foundations of AI: History, Concepts, and Terminology
Duration:00:02:51
A Brief History of Artificial Intelligence: From Turing to Today
Duration:00:04:17
Core Concepts in AI: Understanding the Building Blocks
Duration:00:03:45
Decoding Machine Learning: Techniques and Applications for Coders
Duration:00:04:00
AI and ML Terminology: Essential Vocabulary for the Modern Coder
Duration:00:03:48
The Future of AI and ML in Coding and Beyond
Duration:00:02:43
Chapter Summary
Duration:00:01:35
2. Machine Learning Basics: Supervised, Unsupervised, and Reinforcement Learning
Duration:00:02:03
Supervised Learning: Training with Labeled Data
Duration:00:03:57
Unsupervised Learning: Discovering Hidden Patterns
Duration:00:04:03
Reinforcement Learning: Learning through Interaction
Duration:00:04:17
Comparing and Choosing the Right Learning Method
Duration:00:03:31
Embracing the Power of AI and ML in Coding
Duration:00:02:10
3. Essential Tools and Libraries for AI and ML Development
Duration:00:02:02
Popular Programming Languages for AI and ML
Duration:00:04:12
Machine Learning Libraries and Frameworks
Duration:00:04:08
Data Visualization and Analysis Tools
Duration:00:03:24
Choosing the Right Tools for Your AI and ML Projects
Duration:00:03:37
4. Data Preparation and Preprocessing Techniques for Machine Learning
Duration:00:02:01
Understanding the Importance of Data Quality in Machine Learning
Duration:00:03:20
Data Cleaning and Handling Missing Values
Duration:00:03:58
Feature Engineering and Selection for Optimal Model Performance
Duration:00:03:24
The Impact of Effective Data Preparation on Machine Learning Success
Duration:00:02:28
5. Supervised Learning Algorithms: Regression, Classification, and Decision Trees
Duration:00:03:20
Exploring Regression Techniques for Predictive Modeling
Duration:00:03:40
Delving into Classification Algorithms for Categorical Data
Duration:00:03:44
Unraveling the Power of Decision Trees in Machine Learning
Duration:00:03:34
Practical Applications and Real-World Examples of Supervised Learning
Duration:00:03:40
Harnessing the Potential of Supervised Learning Algorithms for Coders
Duration:00:02:58
6. Unsupervised Learning Algorithms: Clustering, Dimensionality Reduction, and Association Rules
Duration:00:03:00
Clustering Techniques: K-Means, Hierarchical, and DBSCAN
Duration:00:04:18
Dimensionality Reduction Methods: PCA, t-SNE, and UMAP
Duration:00:03:46
Association Rules: Apriori and Eclat Algorithms
Duration:00:04:14
Practical Applications and Real-World Examples
Duration:00:03:39
Harnessing the Power of Unsupervised Learning Algorithms
Duration:00:02:58
7. Deep Learning and Neural Networks: Architectures, Activation Functions, and Training Techniques
Duration:00:03:13
Exploring Various Neural Network Architectures
Duration:00:04:16
Activation Functions: Types and Applications
Duration:00:04:03
Training Techniques for Optimal Performance
Duration:00:04:06
Real-World Applications of AI and ML in Coding
Duration:00:03:29
The Future of Deep Learning and Neural Networks
Duration:00:03:07
8. Natural Language Processing: Text Analysis, Sentiment Analysis, and Chatbots
Duration:00:02:56
Text Analysis Techniques and Applications
Duration:00:04:00
Sentiment Analysis: Understanding Emotions in Text
Duration:00:03:56
Building Chatbots: Conversational AI and User Interaction
Duration:00:04:45
Integrating AI and ML into Your NLP Projects
Duration:00:04:07
The Future of Natural Language Processing and Its Impact on Coders
Duration:00:03:06
9. Computer Vision and Image Recognition: Convolutional Neural Networks and Object Detection
Duration:00:03:10
Exploring Convolutional Neural Networks: Architecture and Applications
Duration:00:04:33
Object Detection Techniques: From Traditional Methods to Deep Learning Approaches
Duration:00:04:35
Implementing Convolutional Neural Networks for Image Recognition Tasks
Duration:00:04:52
Real-World Applications and Case Studies in Computer Vision
Duration:00:03:40
The Future of Computer Vision and Image Recognition in AI and ML
Duration:00:03:23
10. Ethical Considerations and Responsible AI Development
Duration:00:02:43
Understanding Bias and Fairness in AI and ML Algorithms
Duration:00:04:11
Privacy and Data Security: Safeguarding User Information
Duration:00:03:30
Transparency and Explainability: Building Trust in AI Systems
Duration:00:03:51
Accountability and Regulation: Ensuring Responsible AI Development
Duration:00:03:19
The Future of Ethical AI and ML for Coders
Duration:00:02:32