Bøger af Prateek Joshi

Arthroplasty market is expected to grow at a compound annual growth rate of 26.7% during 2010-2017. Almost 70,000 joint replacement surgeries were performed in India alone in the year of 2011. This rise in joint replacement surgeries is due to increase in average age of population, economic progress of population in general & more Knee Arthroplasty trained Surgeons. In 1997 the WHO formally recognized obesity as a global epidemic. As of 2008 the WHO estimates that at least 500 million adults (greater than 10%) are obese, with higher rates among women than men. The percentage of adults affected in the United States as of 2015-2016 is about 39.6% overall (37.9% of males and 41.1% of females).Hence, in today's era, we are more likely to face challenge of increase in need for knee replacement surgery in morbidly obese patients. This book contains a matched prospective study discussing in detail results of knee replacement surgery in morbidly obese patients.

OpenCV is mainly used in Computer Vision and image processing and is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. This book will be your guide to understanding the basic OpenCV concepts and algorithms.

From installing OpenCV to applying geometric transformations to images and reconstructing a 3D real-world scene from images, this book will help you develop the skills needed to develop computer vision applications with the most popular computer vision library- OpenCV.

Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and ...

Explore the great features of the all-new JIRA 7 to manage projects and effectively handle bugs and software issuesKey Features Updated for JIRA 7, this book covers all the new features introduced in JIRA 7 with a dedicated chapter on JIRA Service Desk-one of the biggest new add-ons to JIRA This book lays a strong foundation to work with agile projects in JIRA from both the administrator and end user's perspective Learn to solve challenging data science problems by building powerful machine learning models using PythonBook DescriptionMachine learning is increasingly spreading in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. Machine learning is transforming the way we understand and interact with the world around us.In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms.The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you'll acquire a broad set of powerful skills in the area of feature selection and feature engineering.The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python.This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice.This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Python Machine Learning Cookbook by Prateek Joshi Advanced Machine Learning with Python by John Hearty Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca MassaronWhat you will learn Use predictive modeling and apply it to real-world problems Understand how to perform market segmentation using unsupervised learning Apply your new-found skills to solve real problems, through clearly-explained code for every technique and test Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms Increase predictive accuracy with deep learning and scalable data-handling techniques Work with modern state-of-the-art large-scale machine learning techniques Learn to use Python code to implement a range of machine learning algorithms and techniquesWho this book is forThis Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected.