Mastering Machine Learning and Deep Learning with Python, Scikit-Learn, and TensorFlow 3rd Edition

Machine learning and deep learning are rapidly evolving fields that are revolutionizing various industries. This comprehensive guide provides an in-depth understanding of these cutting-edge technologies using Python, Scikit-Learn, and TensorFlow 3rd Edition. Whether you are a beginner or an experienced practitioner, this book will equip you with the knowledge and skills to become proficient in data science and artificial intelligence.

Through this comprehensive guide, you will gain a deep understanding of the following concepts:

• Fundamental concepts of machine learning and deep learning
• Supervised and unsupervised learning algorithms
• Model selection, evaluation, and optimization techniques
• Practical applications of machine learning and deep learning
• Real-world examples and case studies

This book is designed for:

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

by Sebastian Raschka

4.5 out of 5

Language	:	English
File size	:	24261 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	1285 pages
X-Ray for textbooks	:	Enabled

FREE

• Data scientists and analysts
• Software engineers and programmers
• Students and researchers in computer science and related fields
• Individuals seeking to enhance their skills in machine learning and deep learning

Chapter 1: to Machine Learning and Deep Learning

• Overview of machine learning and deep learning
• Types of machine learning algorithms
• Applications of machine learning and deep learning

Chapter 2: Supervised Learning

• Linear regression
• Logistic regression
• Decision trees
• Support vector machines

Chapter 3: Unsupervised Learning

• Clustering
• Dimensionality reduction
• Anomaly detection

Chapter 4: Model Selection, Evaluation, and Optimization

• Model selection techniques
• Model evaluation metrics
• Optimization algorithms

Chapter 5: Practical Applications of Machine Learning

• Natural language processing
• Computer vision
• Speech recognition

Chapter 6: Deep Learning

• Neural networks
• Convolutional neural networks
• Recurrent neural networks

Chapter 7: TensorFlow 3rd Edition

• to TensorFlow
• Building and training machine learning models
• Deploying machine learning models

Chapter 8: Real-World Examples and Case Studies

• Case study: Building a spam email classifier
• Case study: Developing a facial recognition system

• Develop a solid foundation in machine learning and deep learning
• Master the practical applications of these technologies
• Enhance your data science and artificial intelligence skills
• Gain hands-on experience with Python, Scikit-Learn, and TensorFlow 3rd Edition
• Prepare for a successful career in data science and artificial intelligence

This comprehensive guide will empower you to harness the power of machine learning and deep learning to solve complex data-driven problems. With its clear explanations, practical examples, and real-world case studies, this book will guide you on your journey to becoming a proficient data scientist or artificial intelligence engineer.

• GitHub Repository
• Packt Publishing

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

by Sebastian Raschka

4.5 out of 5

Language	:	English
File size	:	24261 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	1285 pages
X-Ray for textbooks	:	Enabled

FREE