Python for Machine Learning: From Fundamentals to Real-World ApplicationsКНИГИ » ПРОГРАММИНГ
Название: Python for Machine Learning: From Fundamentals to Real-World Applications Автор: Kameron Hussain, Frahaan Hussain Издательство: Sonar Publishing Год: November 10, 2023 Страниц: 362 Язык: английский Формат: pdf, epub (true), mobi Размер: 10.2 MB
"Python for Machine Learning: From Fundamentals to Real-World Applications" is your comprehensive roadmap to mastering Machine Learning with Python. Whether you're a beginner looking to enter the exciting world of Data Science or an experienced programmer aiming to delve deeper into Machine Learning, this book provides you with the knowledge and practical skills needed to excel in the field.
Starting with the fundamentals, you'll learn the essential concepts of Machine Learning and get a solid grasp of Python programming. As you progress, you'll explore the core Machine Learning algorithms, data preprocessing techniques, and Python libraries that are crucial for building predictive models. From linear regression and decision trees to neural networks and Deep Learning, this book covers a wide range of Machine Learning topics.
Machine Learning (ML) is a subfield of Artificial Intelligence (AI) that focuses on the development of algorithms and statistical models that enable computers to learn and make predictions or decisions without being explicitly programmed. In traditional programming, humans write explicit instructions for a computer to perform specific tasks. However, in machine learning, the computer learns from data and experiences to improve its performance on a particular task.
Key Features:
Build a strong foundation in Python programming and data manipulation. Understand the key concepts and algorithms of machine learning. Apply machine learning techniques to real-world problems and datasets. Explore popular Python libraries like scikit-learn, TensorFlow, and Keras. Gain insights into model evaluation, hyperparameter tuning, and feature selection. Work on hands-on projects and develop a portfolio of machine learning applications.
"Python for Machine Learning" doesn't stop at theory; it takes you through practical, real-world applications. You'll work on projects that involve image recognition, natural language processing (NLP), recommendation systems, and more. By the end of the book, you'll have the confidence to tackle complex Machine Learning challenges and contribute to cutting-edge Data Science projects.
Whether you aspire to become a data scientist, machine learning engineer, or simply want to harness the power of Machine Learning in your current role, this book is your key to unlocking the vast potential of Python for Machine Learning.
Chapter 1: Introduction to Machine Learning with Python Chapter 2: Data Preprocessing and Exploration Chapter 3: Supervised Learning: Regression Chapter 4: Supervised Learning: Classification Chapter 5: Unsupervised Learning: Clustering Chapter 6: Dimensionality Reduction Chapter 7: Model Selection and Hyperparameter Tuning Chapter 9: Neural Networks and Deep Learning Chapter 10: Natural Language Processing with Python Chapter 12: Time Series Analysis and Forecasting Chapter 13: Reinforcement Learning Chapter 14: Model Deployment and Serving Chapter 15: Ethics and Bias in Machine Learning Chapter 16: Real-World Machine Learning Projects Chapter 17: Case Studies in Industry
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