Angielski
Build Machine Learning models with a sound statistical understanding.
Key Features:
Book Description:
Complex statistics in machine learning worry a lot of developers. Knowing statistics helps you build strong machine learning models that are optimized for a given problem statement.
This book will teach you all it takes to perform the complex statistical computations that are required for machine learning. You will gain information on the statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. You will see real-world examples that discuss the statistical side of machine learning and familiarize yourself with it. You will come across programs for performing tasks such as modeling, parameter fitting, regression, classification, density collection, working with vectors, matrices, and more.
By the end of the book, you will have mastered the statistics required for machine learning and will be able to apply your new skills to any sort of industry problem.
What You Will Learn:
Who this book is for:
This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful.
