In the preceding chapters, you saw how you can extract, process, and transform data to convert it to a form suitable for learning using Machine Learning algorithms. This chapter deals with the most important part of using that processed data, to learn a model that you can then use to ...
Practical Machine Learning with Python.pdf The availability of affordable compute power enabled by Moore’s law has been enabling rapid advances in Machine Learning solutions and driving adoption across diverse segments of the industry. The ability to learn complex models underlying the real-world ...
Practical Machine Learning with Pythonfollows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and...
This book is a quick start guide for data scientists and machine learning engineers looking to implement machine learning models for streaming data with Python to generate real-time insights. You'll start with an introduction to streaming data, the various challenges associated with it, some of ...
Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code.Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts ...
with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-...
Python Machine learning Psychological applications Regression models Tutorial 1. Introduction In the dynamic field of psychology, the emergence of ML represents a significant change, blending the areas of computer science with human behavior and cognitive processes. ML, as a subset of artificial intellige...
Explore the world of using machine learning methods with deep computer vision, sensors and data in sports, health and fitness and other industries. Accompanied by practical step-by-step Python code samples and Jupyter notebooks, this comprehensive guide acts as a reference for a data scientist, ma...
in deep learning algorithms feature engineering is done automatically by the algorithm. Feature engineering is difficult, time-consuming and requires domain expertise. The promise of deep learning is more accurate machine learning algorithms compared to traditional machine learning with less or no feature...
with machine learning. it teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in python machine learning ecosystems. the book also focuses on building a foundation of machine learning knowledge to solve different real-...