Core Machine Learning and Deep Learning : Supervised, Unsupervised, Reinforcement Learning, Neural Networks, Optimization, and Transfer Learning
Overview
This all-in-one resource walks you through the full spectrum of machine learning. From foundational math to supervised, unsupervised, and reinforcement learning, it provides a thorough understanding of core ML and DL principles. Ideal for both beginners and advancing practitioners, it includes hands-on tools, practical algorithms, and insights into neural networks and optimization techniques. What's Inside?
✔ Regression, classification, and ensemble models
✔ Clustering, anomaly detection, and dimensionality reduction
✔ Reinforcement learning: Q-learning, DQNs, and MDPs
✔ Neural networks: MLPs, backpropagation, and activation functions
✔ Optimization: SGD, Adam, and regularization
✔ Transfer learning, feature extraction, and deployment
✔ Bias-variance tradeoff and model evaluation Why This Book?
Because understanding the core mechanics of learning systems is key to building reliable, ethical, and high-performing AI models.
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Details
- ISBN-13: 9798291198339
- ISBN-10: 9798291198339
- Publisher: Independently Published
- Publish Date: July 2025
- Dimensions: 9 x 6 x 0.36 inches
- Shipping Weight: 0.51 pounds
- Page Count: 168
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