Building Machine Learning Systems with Python

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Get more from your data by creating practical machine learning systems with Python. This third edition addresses recent developments in the field, covering popular datasets and libraries essential for building machine learning systems. Machine learning enables systems to learn without explicit programming, and Python's extensive library support makes it a leading choice for developing applications. This book guides you through finding patterns in raw data, starting with a review of Python machine learning concepts and libraries. You'll engage in real-world projects involving modeling and recommendation systems. By the end, you'll be equipped to build your own systems tailored to solve real-world data analysis problems using techniques such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks. Learn to build classification systems for text, images, and sound, utilize Amazon Web Services (AWS) for cloud analysis, tackle regression issues with scikit-learn and TensorFlow, recommend products based on user history, and apply deep neural networks to structured data. This resource is ideal for data scientists, machine learning developers, and Python programmers looking to create complex machine learning systems, with prior knowledge of Python programming expected.