Artificial Intelligence (AI) and Machine Learning (ML) – SuperUzer

Artificial Intelligence (AI) and Machine Learning (ML)

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Artificial Intelligence (AI) and Machine Learning (ML)

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Original price was: ₹3,999.00.Current price is: ₹1,999.00.

Say goodbye to lengthy workshops and bootcamps. Access our comprehensive eBook, offering lifetime access to this exclusive ebook which deep dives into AI & ML. With this CODE RICH book you can up-skill & lead the way.

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Artificial Intelligence (AI) and Machine Learning (ML)

with fully coded examples, cheat sheets, interview questions with answers & more

Say goodbye to lengthy workshops and bootcamps. Access our comprehensive eBook, offering lifetime access to this exclusive ebook which deep dives into AI & ML. With this CODE RICH book you can up-skill & lead the way.

 

Topics Covered:

Chapter 1: Introduction
Chapter 2: Understanding AI and ML
Chapter 3: Machine Learning
Algorithms Overview
Chapter 4: Regression Techniques in
Machine Learning
Chapter 5: Classification Algorithms for Predictive Modeling
Chapter 6: Clustering Methods for Data Analysis
Chapter 7: Introduction to Neural Networks
Chapter 8: Deep Learning Fundamentals
Chapter 9: Advanced Neural Networks
Chapter 10: Image Recognition Techniques
Chapter 11: Speech Recognition with AI
Chapter 12: Natural Language
Processing Essentials
Chapter 13: Text Processing and Tokenization
Chapter 14: Sentiment Analysis in NLP
Chapter 15: Machine Translation and Chatbots
Chapter 16: Computer Vision Fundamentals
Chapter 17: Image Processing Techniques
Chapter 18: Object Detection and Recognition
Chapter 19: Video Analysis and Tracking
Chapter 20: Introduction to
Reinforcement Learning
Chapter 21: Markov Decision Processes
Chapter 22: Training Models through
Trial and Error
Chapter 23: Applications of Reinforcement
Learning
Chapter 24: AI Ethics and Responsibilities
Chapter 25: Understanding Bias in AI Models
Chapter 26: Fairness in AI Applications
Chapter 27: Mitigating Bias in Machine Learning
Chapter 28: AI in Healthcare Innovations
Chapter 29: Diagnostic Applications of AI
Chapter 30: Treatment Planning with AI
Chapter 31: AI for Patient Care and Monitoring
Chapter 32: Techniques for AI Model Optimization
Chapter 33: Hyperparameter Tuning Methods
Chapter 34: Model Evaluation and Validation
Chapter 35: AI Security Challenges
Chapter 36: Protecting AI from Adversarial Attacks
Chapter 37: Ensuring Data Privacy in AI Systems
Chapter 38: AI in Finance Overview
Chapter 39: Risk Assessment Using AI
Chapter 40: AI-Driven Trading Algorithms and Customer Service

 

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