James Chen – författare

JAMES CHEN, CTA, CMT (Montville, NJ) is Chief Technical Strategist at FX Solutions, a leading foreign exchange broker. An expert on forex trading and technical analysis, he is also a registered Commodity Trading Advisor (CTA) and a Chartered Market Technician (CMT). Mr. Chen writes daily currency analysis, leads forex trading seminars, and has authored numerous articles on currency trading strategy and technical analysis for major financial publications. These include Forbes.com, Futures Magazine, Technical Analysis of Stocks and Commodities Magazine, and Stocks, Futures and Options (SFO) Magazine.

JAMES CHEN, CTA, CMT (Montville, NJ) is Chief Technical Strategist at FX Solutions, a leading foreign exchange broker. An expert on forex trading and technical analysis, he is also a registered Commodity Trading Advisor (CTA) and a Chartered Market Technician (CMT). Mr. Chen writes daily currency analysis, leads forex trading seminars, and has authored numerous articles on currency trading strategy and technical analysis for major financial publications. These include Forbes.com, Futures Magazine, Technical Analysis of Stocks and Commodities Magazine, and Stocks, Futures and Options (SFO) Magazine.

Essentials of Technical Analysis for Financial Markets is an all-encompassing handbook on navigating the financial markets successfully using technical analysis. Clearly written, easy-to-understand, and straightforward, this guide focuses on the key information needed by traders and investors to take on any financial market effectively.

With financial markets in "roller coaster" mode, technical analysis offers a unique advantage for managing risk and finding high-probability trading opportunities. Packed with insightful tips and guidance, Essentials of Technical Analysis for Financial Markets provides proven trading strategies from one of today''s top technical strategists.

Essentials of Technical Analysis for Financial Markets is an all-encompassing handbook on navigating the financial markets successfully using technical analysis. Clearly written, easy-to-understand, and straightforward, this guide focuses on the key information needed by traders and investors to take on any financial market effectively.

With financial markets in "roller coaster" mode, technical analysis offers a unique advantage for managing risk and finding high-probability trading opportunities. Packed with insightful tips and guidance, Essentials of Technical Analysis for Financial Markets provides proven trading strategies from one of today''s top technical strategists.

This book is a comprehensive guide to understanding and implementing cutting-edge machine learning and deep learning techniques using Python programming language. Written with both beginners and experienced developers in mind, this book provides a thorough overview of the foundations of machine learning and deep learning, including mathematical fundamentals, optimization algorithms, and neural networks.

Starting with the basics of Python programming, this book gradually builds up to more advanced topics, such as artificial neural networks, convolutional neural networks, and generative adversarial networks. Each chapter is filled with clear explanations, practical examples, and step-by-step tutorials that allow readers to gain a deep understanding of the underlying principles of machine learning and deep learning.

Throughout the book, readers will also learn how to use popular Python libraries and packages, including numpy, pandas, scikit-learn, TensorFlow, and Keras, to build and train powerful machine learning and deep learning models for a variety of real-world applications, such as regression and classification, K-means, support vector machines, and recommender systems.

Whether you are a seasoned data scientist or a beginner looking to enter the world of machine learning, this book is the ultimate resource for mastering these cutting-edge technologies and taking your skills to the next level. High-school level of mathematical knowledge and all levels (including entry-level) of programming skills are good to start, all Python codes are available at Github.com.

This book is a comprehensive guide to learning the basics of computer vision and machine learning using the powerful OpenCV library and the Python programming language. The book offers a practical, hands-on approach to learning the concepts and techniques of computer vision through practical examples. All codes in this book are available on Github.

Through a series of examples, the book covers a wide range of topics including image and video processing, feature detection, object detection and recognition, machine learning, and deep neural networks. Each chapter includes detailed explanations of the concepts and techniques involved, as well as practical examples and code snippets that demonstrate how to implement them in Python. Throughout the book, readers will work through hands-on examples and projects, learning how to build image-processing applications from scratch. 

Whether you are a beginner or an experienced programmer, this book provides a valuable resource for learning computer vision with OpenCV and Python. The clear and concise writing style makes it easy for readers to follow along, and the numerous examples ensure that readers can practice and apply what they have learned. By the end of the book, readers will have a solid understanding of the fundamentals of computer vision and be able to build their own computer vision applications with confidence. This book is an excellent resource for anyone looking to learn computer vision and machine learning using the OpenCV library and Python programming language.

Table of Contents

1.  Introduction

 1.1  About OpenCV

 1.2  Target Audients

 1.3  Source Codes for This Book

 1.4  Hardware Requirements

 1.5  How This Book Organized

2.  Installation

 2.1  Install on Windows

 2.2  Install on Ubuntu

 2.3  Configure PyCharm and Install OpenCV

3.  OpenCV Basics

 3.1  Load and Display Images

 3.2  Load and Display Videos

 3.3  Display Webcam

 3.4  Image Fundamentals

 3.5  Draw Shapes

 3.6  Draw Texts

 3.7  Draw an OpenCV-like Icon

4.  User Interaction

 4.1  Mouse Operations

 4.2  Draw Circles with Mouse

 4.3  Draw Polygon with Mouse

 4.4  Crop an Image with Mouse

 4.5  Input Values with Trackbars

5.  Image Processing

 5.1  Conversion of Color Spaces

 5.2  Resize, Crop and Rotate an Image

 5.3  Adjust Contrast and Brightness of an Image

 5.4  Adjust Hue, Saturation and Value

 5.5  Blend Image

 5.6  Bitwise Operation

 5.7  Warp Image

 5.8  Blur Image

 5.9  Histogram

6.  Object Detection

 6.1  Canny Edge Detection

 6.2  Dilation and Erosion

 6.3  Shape Detection

 6.4  Color Detection

 6.5  Text Recognition with Tesseract

 6.6  Human Detection

 6.7  Face and Eye Detection

 6.8  Remove Background

 6.9  Blur Background

7.  Machine Learning

 7.1  K-Means Clustering

 7.2  K-Nearest Neighbors

 7.3  Support Vector Machine

 7.4  Artificial Neural Network (ANN)

 7.5  Convolutional Neural Network (CNN)

References

About the Author