Other books that might interest you

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  Natural Cosmetic Formulation:...

  Alice Burrell

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  Save money now and learn how to make your own cosmetics at home! 
  Wouldn’t it be amazing if you could make your own beauty products? 
  You could have complete control over what goes into your cosmetics and be confident that they are just the way you like them. 
  And wouldn’t it be incredible if you could start a side business and sell something you’ve created with your own hands? 
  Making cosmetics sounds very difficult, whereas, in reality, it is a very easy process that can turn into a productive hobby. 
  With some pointers and tips from the experts, you can get started with making your favorite cosmetics much less expensive than store-bought. 
  All it takes are some normal cooking utensils, a few basic ingredients, and a little bit of time. 
  In this audiobook, you’ll:Uncover the chemistry behind product formulationUnderstand how you can do things like making emulsions at home with minimal gearFamiliarize yourself with the core principles of cosmetic manufacturingLearn to preserve your creations with preservatives and antioxidantsMaster different recipes to create all kinds of productsAchieve so much knowledge that you’ll be able to make customized products that meet your exact needs 
  If you suffer from a particular medical condition or off-the-shelf products don’t seem to be working well for you, there’s no reason to fret! With the guidelines in this audiobook and experts’ actionable advice, you can start making your own products today. 
  So, click the “add to cart” button and don’t spend another dollar on cosmetics when you can easily make them yourself at home.

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  Advabced Scrum Case Studies Vol...

  Frederik Mark Fowler

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  You are an Agile Coach and you are being called in to fix a problem with project ownership.  There is a team of developers who look good on paper but who are not performing up to expectations.  They do not seem to care very much about the work they are doing.  You have been asked to figure out what is wrong and to fix it. 
  What should you do? 
  This case and the others in the series come from the real-world experiences of a group of Scrum professionals who meet regularly to discuss the Scrum Framework and how to apply it to actual situations they have encountered.  These discussions have been led since 2015 by Frederik Mark Fowler, A Doctor of Scrum and Holder of the Professional Scrum Master level III certification awarded by Scrum.org.  Fred has worked with the Scrum Framework for almost 20 years and has trained more then 300 people to become Scrum Masters and Product Owners.  For more information, visit www.Patreon.com/SiliconValleyScrum.

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  Snake Men - Rebels Reptiles and...

  Zach St. George

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  A wry and thought-provoking tale about the defiant, eccentric figures obsessed with Australia's deadliest reptiles. 
  Raymond Hoser is known as the Snakeman, a moniker he has zealously defended. As a day job, Hoser runs a business in Melbourne that offers several services. One service is snake removal, a common trade in Australia. Another is snake shows, most often performed at children's birthday parties. But by the 2010s, Hoser had become famous around the world for an entirely different activity: his work as a taxonomist, a namer of new species. In a decade-long spree, Hoser had named thousands of new creatures, including more snakes than any other scientist. To some, Hoser's accomplishments were a scientific triumph. But others have accused Hoser of what they call "taxonomic vandalism," the results of which, they argue, could alter the very course of life on Earth. 
  Snake Men recounts this outrageous and humorous story, tracing the surprising intersection between taxonomists, the sober and serious class of scientists who have for centuries cooperated in a global effort to understand the order of life, and Raymond Hoser and other snake men. The results―chaotic, mischievous, the stuff of legends―hint at the rebellious impulse that lies coiled somewhere deep inside us all.

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  Dividing Lines - How...

  Deborah N. Archer

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  Our nation's transportation system is crumbling. But as acclaimed scholar and ACLU president Deborah Archer warns in Dividing Lines, before we can think about rebuilding and repairing, we must consider the role race has played in transportation infrastructure, from the early twentieth century and into the present day. 
   
   
   
  As Archer demonstrates, the success of the Civil Rights movement and the fall of Jim Crow in the 1960s did not mean the end of segregation. With state-sanctioned racism no longer legal, officials across the country turned to transportation infrastructure to keep Americans divided. A wealthy white neighborhood could no longer be "protected" by racial covenants and segregated shops, but a multilane road, with no pedestrian crossings, could be built along its border to make it difficult for people from a lower-income community to visit. Highways could not be routed through Black neighborhoods based on the race of their residents, but those neighborhoods' lower property values—a legacy of racial exclusion—could justify their destruction. 
   
   
   
  Drawing on a wealth of sources, including interviews with people who now live in the shadow of highways and other major infrastructure projects, Archer presents a sweeping, national account—from Atlanta and Houston to Indianapolis and New York City—of our persistent divisions.

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  Hands-on ML Projects with OpenCV

  Mugesh S.

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  Be at your A game in building Intelligent systems by leveraging Computer vision and Machine Learning. 
  
  KEY FEATURES 
  - Step-by-step instructions and code snippets for real world ML projects. 
  - Covers entire spectrum from basics to advanced concepts such as deep learning, transfer learning, and model optimization
  - Loaded with practical tips and best practices for implementing machine learning with OpenCV for optimising your workflow. 
  
  DESCRIPTION
  This book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in a step-by-step manner using code and output snippets. 
  
  Hands-on projects with real-world datasets will offer you an invaluable experience in solving OpenCV challenges with machine learning. It’s an ultimate guide to explore areas like deep learning, transfer learning, and model optimization, empowering readers to tackle complex tasks. Every chapter offers practical tips and tricks to build effective ML models. 
  
  By the end, you would have mastered and applied ML concepts confidently to real-world computer vision problems and will be able to develop robust and accurate machine-learning models for diverse applications. 
  
  Whether you are new to machine learning or seeking to enhance your computer vision skills, This book is an invaluable resource for mastering the integration of machine learning and computer vision using OpenCV and Python. 
  
  WHAT WILL YOU LEARN 
  - Learn how to work with images and perform basic image processing tasks using OpenCV. 
  - Implement machine learning techniques to computer vision tasks such as image classification, object detection, and image segmentation. 
  - Work on real-world projects and datasets to gain hands-on experience in applying machine learning techniques with OpenCV. 
  - Explore the concepts of deep learning using Tensorflow and Keras and how it can be used for computer vision tasks. 
  - Understand the concept of transfer learning and how pre-trained models can be leveraged for new tasks. 
  - Utilize techniques for model optimization and deployment in resource-constrained environments. 
  - Implement end-to-end solutions and address challenges encountered in practical scenarios. 
  
  WHO IS THIS BOOK FOR?
  This book is for everyone with a basic understanding of programming and who wants to apply machine learning in computer vision using OpenCV and Python. Whether you're a student, researcher, or developer, this book will equip you with practical skills for machine learning projects. Some familiarity with Python and machine learning concepts is assumed. Beginners too will find this book valuable as it offers clear examples and explanations for every concept. 
  
  TABLE OF CONTENTS 
  Chapter 1: Getting Started With OpenCV 
  Chapter 2: Basic Image & Video Analytics in OpenCV
  Chapter 3: Image Processing 1 using OpenCV
  Chapter 4: Image Processing 2 using OpenCV
  Chapter 5: Thresholding and Contour Techniques Using OpenCV 
  Chapter 6: Detect Corners and Road Lane using OpenCV
  Chapter 7: Object And Motion Detection Using Opencv
  Chapter 8: Image Segmentation and Detecting Faces Using OpenCV
  Chapter 9: Introduction to Deep Learning with OpenCV
  Chapter 10: Advance Deep Learning Projects with OpenCV
  Chapter 11: Deployment of OpenCV projects

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  The AI Strategy Framework for...

  David M. Patel

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  Want to use AI for business, but unsure where to start? Tired of hype and need actionable steps? Need a Leader's Guide to AI Strategy?Amazon-bestselling author David M. Patel reveals a hands-on guide to designing and implementing a winning AI roadmap. Whether leading a global organization or a growing team, this playbook unlocks the frameworks to translate AI potential into real business results—no technical background required!What You'll Discover Inside:Part I – AI Imperative & Strategic FoundationsWhat AI Strategy Is & Why It's Non-Negotiable.The AI Business Revolution: How We Got Here.Why Every Leader Needs to Drive AI Strategy (No Tech Expertise Needed!).Key Concepts (ML, GenAI) Explained Simply.Harnessing Strategic Opportunities in 2025 & Beyond.Part II – Your AI Strategy ToolkitThe 5 Core Pillars of a Robust Strategy.Practical Frameworks to Assess Readiness.Step-by-Step: Defining Vision & Business Alignment.Prioritizing High-Impact Use Cases (With Worksheets!).Building a Smart Data Strategy.Creating an AI-Ready Team: Build, Buy, or Partner?Part III – Implementing & MeasuringProject 1: Launching Your First AI Pilot.Project 2: Scaling Initiatives for Maximum Impact.Project 3: Embedding Responsible AI & Governance.Measuring ROI: Metrics That Show Real Value.Managing Risks, Security & Compliance.Fostering a Culture of Ongoing Innovation.Even if you feel overwhelmed, this guide breaks everything down into clear, manageable steps. Get the insights, tools, and confidence to lead your organization into the future.The AI-Powered Future Is Here. Don't let complexity hold you back. Grab your copy today and start implementing a strategy that drives impact, innovation, and success!

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