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Free chapter link - Efficient Linux at the Command Line, Ch 4
If you want to work smarter (and faster), the techniques in this chapter will help you quickly navigate the Linux filesystem with less typing. They are simple to use but have enormous bang for the buck, with small learning curves and big payoffs. And this chapter is free, our gift to you.
Free chapter link - Practical Machine Learning for Computer Vision, Ch 3
Using machine learning models to extract information from images is one of the trickiest ML tasks—but it often yields invaluable insights. What’s more, image classification is the “Hello World” of deep learning: It’s a stepping stone to other deep learning domains, such as natural language processing. In chapter 3, the authors of Practical Machine Learning for Computer Vision lay out the techniques and model architectures that take advantage of the special properties of images. And did we mention, it’s free?
Free chapter link - Practical Python Data Wrangling and Data Quality, Ch 4
Without the ability to extract, evaluate, and analyze a wide variety of data sources and formats, your mountains of data are worthless. This essential guide clearly explains how to easily clean, evaluate, and analyze data so you can generate meaningful insights and compelling visualizations. Chapter 4 covers working with file-based and feed-based data in Python—and you can get it free today as our gift to you.
Free chapter link - Software Engineering at Google, Ch 4
There’s a growing imperative for engineers to design products that work for everyone. But being aware of the impact your product has on users from underrepresented communities and building safeguards into the design from the beginning can be complicated. Chapter 4 from Software Engineering at Google shows how to engineer products that empower and respect all users. And you can get it free today, our gift to you.
Free chapter link - The Manager's Path, Ch 3
If you’re a tech lead—or are responsible for promoting someone to fill that role—this chapter’s for you. It dives into what a tech lead does, how the job should be structured, how to manage projects, and most importantly, what makes a tech lead successful. And today, you can get chapter 3, Tech Leads, free, as our gift to you.
Playlist link - Kubernetes Playlist from Basics to Guru - Sander van Vugt
Learn Kubernetes and then get certified! This playlist will teach you how to run orchestrated containers in the cloud or on premise. Go from basic concepts to hands-on experience and then get your CKAD and CKA certs. This playlist leads you from basics to advanced techniques.
Playlist link - Linux: From Basics to Guru - Sander van Vugt
Welcome to Sander van Vugt's Linux: From Basics to Guru Playlist. This playlist leads you through basic Linux concepts to advanced techniques and prepares you to take multiple Red Hat certification exams.
Playlist link - Ansible: From Beginner to Certification - Sander van Vugt
Welcome to Sander van Vugt’s guide to learning Ansible and then getting certified! This playlist will teach you how to use Ansible to simplify your configuration management. This playlist leads you from basics to advanced techniques and also prepares you to take the RHCE EX294 certification.
Course link - Red Hat Certified System Administrator (RHCSA) RHEL 9 with Sander van Vugt
Red Hat Certified System Administrator (RHCSA) RHEL 9 Complete Video Course is your complete study toolkit to get exam ready for the RHCSA RHEL 9 exam. This 14-hour course is also a great resource for anyone who wants to enhance their Linux skills to grow their career. Expert trainer and author Sander van Vugt provides topic-focused coverage of all objectives in the exam, drilling down on important concepts like Bash Shell, storage, containers, and advanced system administration tasks. You will also get real-world labs in each lesson so you can practice your skills; along with video solutions so you can assess your progress as you move through the course. The course ends with a practice exam so you can fully prepare for test day.
Video link - Search logs + machine learning = autotagged inventory - John Berryman
John Berryman takes a deep dive into the problem space and Eventbrite’s approach. He explores how the company gathered training data from its search and click logs, and how it built and refined the model. You’ll see the output of the model and both the positive results of Eventbrite’s work, as well as the work left to be done. You’ll leave with some new ideas to take back to your business.
Get a Demo of oreilly.com
Help your tech teams stay ahead of what’s next See the O’Reilly learning platform in action O’Reilly has been sharing the knowledge of innovators to help tech teams for over 40 years. But we also offer droves of content to help with project management, leadership training, and more.
Microsoft Power Platform Essentials Playlist Jason Rivera
Jason Rivera spotlights resources to help you use the Microsoft Power Platform to build end-to-end solutions that address tactical business needs.
Book-Generative AI on AWS
You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images.
Generative AI in the Real World: Kingsley Ndoh on Improving Cancer Care with AI
What can AI do to improve healthcare? Kingsley Ndoh, founder of Hurone AI, talks with Ben Lorica about how Hurone is making cancer care more effective for people who are underserved by the medical system. He discusses how AI can streamline the medical process, both helping doctors to treat patients more effectively and making clinical trials more diverse.About the Generative AI in the Real World podcast: In 2023, ChatGPT put AI on everyone’s agenda. In 2024, the challenge will be turning those agendas into reality. In Generative AI in the Real World, Ben Lorica interviews leaders who are building with AI. Learn from their experience to help put AI to work in your enterprise.Points of Interest0:00: Introduction.0:36: What motivated you to apply AI to cancer care? What problems are you trying to solve?1:39: We need environments for training AI models that are effective for all populations.2:31: Current oncology solutions serve advanced healthcare systems, leaving community oncology centers and international markets underserved.3:31: Lack of diversity in clinical trials means we don’t have full evidence on the efficacy of drugs.5:00: What is an oncologist?6:10: Cancer is a very complex disease; every cancer is different and has its own solutions.6:43: What advantages do you bring as a domain expert?7:11: I’ve been a physician taking care of patients. I understand clinical workflows in Nigeria and the US. I’ve also been an entrepreneur since I was in high school. I’ve also worked in the global oncology space with governments and pharma companies. That network is very important.9:15: What was the situation before Gukiza [Hurone’s app]? What does Gukiza enable today?9:44: Gukiza makes care more accessible to patients and optimizes workflows for oncologists. They may have to travel long distances to see an oncologist; they may have side effects or even emergencies that are avoidable; data about events may be lost.12:53: Gukiza streamlines the process; it’s a two-way system that can be used standalone. There is a HIPPA-compliant API that can be integrated into major electronic medical records systems. Patients aren’t limited to an app; there is an API for WhatsApp, Telegram, and text messaging.14:13: Patients can describe their problems. Clinicians can click a button and generate a response that they can review and send to the patient. Clinicians can also call patients, do clinical summaries, and see how patients are progressing.17:08: One should think about this as a copilot. The app makes suggestions; the physician makes the decision.17:35: There are definitely risks. We are building our model and fine-tuning it to ensure that hallucination is limited. But there is still a final human review.18:40: What if I want to use the system in a completely new country? What does it take to get the system into a viable, usable state?19:41: We conform to the country’s guidelines for the management of patients. Cancer care is usually based on established guidelines. In the US, we have NCCN guidelines. To make sure guidelines are responsive to different regions, the NCCN looked at evidence for research done in different countries to harmonize guidelines. That gave birth to the resource stratified guidelines for regions like Sub-Saharan Africa. We don’t need to customize a lot.21:38: We are also building agreements for access to de-identified cancer data. As we scale, it will get better.24:02: Health data is the most sensitive data in the world, but also the most abundant. Compared to other industries, healthcare is lagging behind. But many regions are looking for disruption and innovation and are willing to be flexible to work with us.25:20: Our solution isn’t a magic bullet, but it will shift the needle.
Free Report--The State of Security in 2024 V3
The State of Security in 2024: The threats security teams face and the defenses they’re building to beat themO’Reilly’s Mike Loukides considers the state of the field, analyzing data drawn directly from security team members themselves. Dive in to discover the threats that concern frontline practitioners most, the projects they’re implementing to safeguard systems and infrastructure, the skills companies are hiring for (and the certifications they require to verify them), and more.Labels: Security,o'reilly,2024,report,lead,
Computer Vision Fundamentals: Implementing Computer Vision Techniques Using Deep Learning
Computer Vision Fundamentals is an extensive exploration of how artificial intelligence, with a specific focus on deep learning, is driving significant advances in the field of computer vision. This course melds theory and practice, introducing everything from the foundational aspects of image processing to the hands-on implementation of advanced deep learning models in PyTorch, including applications on edge devices.In a progressively digital and data-driven world, processing, analyzing, and deriving insights from vast quantities of visual data is crucial. This course will provide you with the requisite skills and knowledge to apply computer vision techniques to a wide array of sectors, such as autonomous vehicles, facial recognition systems, medical imaging, and edge computing.The course begins with a thorough introduction to computer vision, image processing, and deep learning. It offers an understanding of how these disciplines interconnect and how deep learning enhances traditional computer vision tasks. You will then delve into the foundational mathematics that underpins neural networks and how to implement these networks using the PyTorch framework.From there, you will start building advanced computer vision applications using PyTorch, including convolutional neural networks for image classification, object detection with YOLO, semantic segmentation with U-Net, and pose estimation. Each topic will provide you with both theoretical knowledge and hands-on coding experience, ensuring a comprehensive understanding of the subject matter.Further enhancing your practical skills, the course will turn to real-world case studies. By exploring how deep learning and computer vision techniques are applied in facial recognition systems, autonomous vehicles, and medical imaging, you'll gain insight into the transformative impact of these technologies in various industries.Finally, you will engage with the principles of Machine Learning Operations (MLOps) in the context of computer vision, learning to manage machine learning life cycles efficiently. The course closes by investigating the challenges and solutions of applying MLOps in computer vision projects, such as handling image data, model explainability, and deploying computer vision models in production environments.By the end of this course, you will have a well-rounded understanding of the fundamental concepts, underlying mathematics, and practical applications of computer vision and deep learning. You will be equipped with the tools and knowledge to implement these models and solve real-world problems, giving you a competitive advantage in your software development or data science career.What you’ll learn—and how you can apply itUnderstand the fundamental concepts of computer vision and deep learning and their interrelationBecome proficient in creating, training, and evaluating various types of neural networks, including convolutional neural networks, vision transformers, and generative adversarial networks using the PyTorch frameworkBecome capable of implementing advanced computer vision techniques such as object detection, semantic segmentation, and pose estimation using PyTorchBecome adept at applying computer vision and deep learning techniques to solve real-world problems and evaluate their performanceUnderstand the concept of edge computing in computer vision, be able to apply MLOps principles for managing machine learning lifecycle in deep learning and computer vision projects and recognize future trends in the field of computer vision and deep learningThis video course is for you because…You're a software developer interested in learning to leverage deep learning models, particularly in computer vision, to build AI-powered applications.You're looking to transition from a traditional software development role into a specialized artificial iLabels: Richmond Alake,data,computer Vision,video,
What We Learned from a Year of Building with LLMs Part 1
Over the past year, LLMs have become “good enough” for real-world applications.
What We Learned from a Year of Building with LLMs Part 2
Over the past year, LLMs have become “good enough” for real-world applications.
Rising Tide Rents and Robber Baron Rents
The Replacement of Organic Search with Advertising by Google and Amazon and What That Might Mean for the Future of AI
Fundamentals of DevOps and Software Delivery
Fundamentals of DevOps and Software Delivery is a guide to DevOps and software delivery: that is, a guide to the numerous tools and techniques that are required to take that application code and run it and maintain it in production, where it can generate value for your users and your company on an ongoing basis. This includes going through all the modern practices for deploying applications and microservices to the cloud, managing your infrastructure as code, automating your software delivery lifecycle in a CI/CD pipeline, configuring networking, setting up data stores, and hooking up monitoring.
How to Fix “AI’s Original Sin”
O'Reilly Radar article --Last month, The New York Times claimed that tech giants OpenAI and Google have waded into a copyright gray area by transcribing the vast volume of YouTube videos and using that text as additional training data for their AI models despite terms of service that prohibit such efforts and copyright law that the Times argues places them in dispute.
Report link - The State of Machine Learning Adoption in the Enterprise
Download this free ebook now to see how data scientists, machine learning engineers, and deep learning engineers throughout the world answered detailed questions about their organization’s level of ML adoption. About half of the respondents work for enterprises in the early stages of exploring ML, while the rest have moderate or extensive experience deploying ML models to production. So you get a deep understanding of the methodologies and metrics used throughout the process.Labels: Ai/ml,generative Ai,o'reilly,ai,report,machine Learning,
Course link - Linux Fundamentals, 2nd Edition with Sander van Vugt
Linux Fundamentals LiveLessons has more than 10 hours of comprehensive video training for you to find everything you need to build a strong understanding of working with Linux. This comprehensive video course includes coverage of Linux basics, concepts, practices, and theories, so you can get the foundational knowledge of Linux you need to start your Linux career.Labels: Courses,system Administration,o'reilly,linux,
Head First HTML5 Programming
Head First HTML5 Programming is your ultimate tour guide to creating web applications with HTML5 and JavaScript, and we give you everything you need to know to build them, including: how to add interactivity to your pages, how to communicate with the world of Web services, and how to use the great new APIs being developed for HTML5.Labels: O'reilly Media,elisabeth Robson,ebook,eric Freeman,html5,o'reilly,book,html,programming,head First,
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