Price: $3.99
(as of Dec 27,2024 06:44:16 UTC – Details)
ASIN : B07F6Z2ZKJ
Publication date : July 10, 2018
Language : English
File size : 8488 KB
Simultaneous device usage : Unlimited
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 53 pages
Customers say
Customers find the book helpful and useful for beginners. It explains different concepts clearly with sketches for better explanations. The writing quality is good and the book is written for non-programmers.
AI-generated from the text of customer reviews
Are you interested in learning about machine learning but don’t know where to start? Look no further! In this post, we will provide a step-by-step guide for beginners to understand machine learning concepts and how they are applied in real-life scenarios.
Chapter 1: Introduction to Machine Learning
– What is machine learning and why is it important?
– Types of machine learning: supervised, unsupervised, and reinforcement learning
– Common machine learning algorithms: linear regression, decision trees, and neural networks
Chapter 2: Data Collection and Preprocessing
– Gathering and cleaning data for machine learning models
– Feature engineering techniques to improve model performance
– Handling missing values and outlier detection
Chapter 3: Model Building and Evaluation
– Splitting data into training and testing sets
– Training machine learning models using libraries like scikit-learn and TensorFlow
– Evaluating model performance using metrics like accuracy, precision, and recall
Chapter 4: Model Deployment and Monitoring
– Deploying machine learning models in production environments
– Monitoring model performance and making adjustments as needed
– Understanding ethical considerations and bias in machine learning
By the end of this guide, you will have a solid understanding of the basics of machine learning and how to apply them in practice. Whether you are a student, a data enthusiast, or just curious about this exciting field, Machine Learning in Action: A Primer for The Layman is the perfect introduction to get started. Happy learning!
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