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Coursera - Practical Deep Learning With Python 2025 Course details Welcome to the Practical Deep Learning with Python course, where you'll gain hands-on experience with cutting-edge deep learning techniques to model and ... What you'll learn - Understand the core components of deep learning models and their role in AI. - Apply CNN, R-CNN, and Faster R-CNN for object detection tasks. - Implement RNNs and LSTMs for sequential data processing. - Optimize and evaluate deep learning models for improved performance. There are 4 modules in this course Welcome to the Practical Deep Learning with Python course, where you'll gain hands-on experience with cutting-edge deep learning techniques to model and analyze complex datasets. Unlock the power of deep learning to solve real-world problems and uncover actionable insights from massive data volumes. This course explores industry-specific applications and equips you with the practical skills needed to build and optimize advanced models. By the end of this course, you’ll be able to: - Describe the foundational components of deep learning models and their significance in artificial intelligence. - Illustrate the working of CNNs, R-CNNs, and Faster R-CNNs for object detection and related applications. - Understand the limitations of Perceptrons and how Multi-Layer Perceptrons (MLPs) address them. - Implement Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) architectures for sequential data analysis. - Optimize and evaluate deep learning models to achieve higher accuracy and efficiency. This course is designed for data scientists, machine learning engineers, and AI enthusiasts with a foundational knowledge of Python and machine learning who aim to expand their expertise in deep learning. Experience in building machine learning models, along with knowledge of statistics and proficiency in Python programming, is recommended for this course. Embark on this educational journey to enhance your expertise in deep learning and elevate your capabilities in building intelligent systems for the future of artificial intelligence. General Details: Duration: 6h 10m Updated: 03/2025 Language: English Source: [Hidden Content] Instructor: [Hidden Content] MP4 | Video: AVC, 1920x1080p | Audio: AAC, 44.100 KHz, 2 Ch [Hidden Content]

Indeed, I couldn't agree to it more what exactly battlestar had just said I was research to at least find rumor's post anywhere on the internet to keep a hope, but honestly, it really don't feel good, as far my experience, it's been more than 10 days, any group who wants to stay they would not take that longer to fix the thing such as host, server, or any manner bug or say glitch, 10 days are enough to recover the entire website, in case it was hacked? Or supposed to be rebuilt? 10 days are enough I believe, though, there might be 2 reasons if they don't get back, 1, they don't want to keep it or invest on something that doesn't fulfil their need (which obvious), 2, there is no 2 because it's 2025, nothing hard to get anything back to work, no matter you need a coder, developer, new server, host, domain or even a hacker, so, as far I concerned, reason 1 is obvious, if that's not the cause, then they are out of BUDGET, every task starts and ends here (these are thoughts, I wish they prove me wrong 100%) If I see past, it's similar to every last stand good P2P sources that we had lost recently, Pirateiro, ettv, prostylex, dnoid, same issue budget issue, in fact, KAT/ET had different cause. Anyway, Torrentgalaxy is must need for most of the pirates around the globe, I wish it come back otherwise it shall be uncompleted story for all of us which left no such sense > why they left just like that! > why, many questions remain unsolved!

Da besta musicino week Thank you so much!

Edureka - Applied Machine Learning With Python 2025 Course details This course provides an in-depth, hands-on introduction to machine learning using Python. You'll explore core concepts and methods, diving into supervised, unsupervised, and semi-supervised learning. Through practical exercises and examples, you'll master key algorithms including decision trees and random forests for classification, regression for predictive modeling, and K-means clustering for uncovering hidden patterns in unlabeled data. Additionally, you’ll gain insights into using model-boosting techniques to enhance model accuracy and apply strategies for leveraging unlabeled data effectively. By the end of this course, you’ll be able to: - Explain and implement decision trees and random forests as classification algorithms. - Define and differentiate various types of machine learning algorithms. - Analyze the working of regression for predictive tasks. - Apply K-means clustering to explore and discover patterns in unlabeled data. - Strategically use unlabeled data to improve model training. - Manipulate boosting algorithms to achieve higher model accuracy. This course is ideal for learners with foundational knowledge in Python programming and some familiarity with basic statistical concepts. Prior experience in data analysis or working with data libraries (such as Pandas or NumPy) is beneficial. This course is designed for aspiring data scientists, machine learning enthusiasts, and Python programmers who want to deepen their understanding of machine learning and enhance their data-driven decision-making skills. Equip yourself with practical machine learning skills and advance your journey in AI. Enroll in "Applied Machine Learning with Python" today and bring predictive power to your projects. What you'll learn - Explore machine learning algorithms, including supervised, unsupervised, and semi-supervised methods. - Apply decision trees, random forests, and K-means clustering for classification and clustering. - Develop machine learning models to gain insights and make predictions from real-world data. - Enhance model accuracy by applying model-boosting techniques and evaluating their effectiveness. There are 4 modules in this course This course provides an in-depth, hands-on introduction to machine learning using Python. You'll explore core concepts and methods, diving into supervised, unsupervised, and semi-supervised learning. Through practical exercises and examples, you'll master key algorithms including decision trees and random forests for classification, regression for predictive modeling, and K-means clustering for uncovering hidden patterns in unlabeled data. Additionally, you’ll gain insights into using model-boosting techniques to enhance model accuracy and apply strategies for leveraging unlabeled data effectively. By the end of this course, you’ll be able to: - Explain and implement decision trees and random forests as classification algorithms. - Define and differentiate various types of machine learning algorithms. - Analyze the working of regression for predictive tasks. - Apply K-means clustering to explore and discover patterns in unlabeled data. - Strategically use unlabeled data to improve model training. - Manipulate boosting algorithms to achieve higher model accuracy. This course is ideal for learners with foundational knowledge in Python programming and some familiarity with basic statistical concepts. Prior experience in data analysis or working with data libraries (such as Pandas or NumPy) is beneficial. This course is designed for aspiring data scientists, machine learning enthusiasts, and Python programmers who want to deepen their understanding of machine learning and enhance their data-driven decision-making skills. Equip yourself with practical machine learning skills and advance your journey in AI. Enroll in "Applied Machine Learning with Python" today and bring predictive power to your projects. General Details: Duration: 6h 46m 42s Updated: 03/2025 Language: English Source: [Hidden Content] Instructor: [Hidden Content] MP4 | Video: AVC, 1920x1080p | Audio: AAC, 44.100 KHz, 2 Ch [Hidden Content]

Coursera - NVIDIA: Prompt Engineering and Data Analysis Course details NVIDIA: Prompt Engineering and Data Analysis is the fifth course of the Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs - Associate Specialization. This course equips learners with a solid foundation in prompt engineering, data analysis, and visualization techniques for optimizing Large Language Models (LLMs). The course covers essential concepts such as prompt engineering fundamentals, effective prompt creation, and P-tuning for enhanced LLM performance. It also delves into techniques for analyzing text data, different plot types, and their role in effective data visualization. Learners will gain hands-on experience with tools like NVIDIA NeMo for prompt engineering and cuDF and Dask cuDF for accelerated data analysis workflows. The course is divided into two modules with Lessons and Video Lectures. Learners will engage in approximately 3:00-3:30 hours of video content, covering both theoretical concepts and practical applications. Each module is paired with quizzes to assess understanding and reinforce learning. Module 1: Foundations of Prompt Engineering Module 2: Data Analysis and Visualization By the end of this course, learners will be able to: - Understand prompt engineering and its role in LLM optimization. - Apply P-tuning and RAG architecture for improved model performance. - Utilize data analysis and visualization techniques for effective NLP tasks. This course is ideal for learners interested in enhancing their skills in prompt engineering and data analysis for LLM optimization, with a focus on practical implementation. What you'll learn - Understand prompt engineering and its role in LLM optimization. - Apply P-tuning and RAG architecture for improved model performance. - Utilize data analysis and visualization techniques for effective NLP tasks. There are 2 modules in this course NVIDIA: Prompt Engineering and Data Analysis is the fifth course of the Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs - Associate Specialization. This course equips learners with a solid foundation in prompt engineering, data analysis, and visualization techniques for optimizing Large Language Models (LLMs). The course covers essential concepts such as prompt engineering fundamentals, effective prompt creation, and P-tuning for enhanced LLM performance. It also delves into techniques for analyzing text data, different plot types, and their role in effective data visualization. Learners will gain hands-on experience with tools like NVIDIA NeMo for prompt engineering and cuDF and Dask cuDF for accelerated data analysis workflows. The course is divided into two modules with Lessons and Video Lectures. Learners will engage in approximately 3:00-3:30 hours of video content, covering both theoretical concepts and practical applications. Each module is paired with quizzes to assess understanding and reinforce learning. Module 1: Foundations of Prompt Engineering Module 2: Data Analysis and Visualization By the end of this course, learners will be able to: - Understand prompt engineering and its role in LLM optimization. - Apply P-tuning and RAG architecture for improved model performance. - Utilize data analysis and visualization techniques for effective NLP tasks. This course is ideal for learners interested in enhancing their skills in prompt engineering and data analysis for LLM optimization, with a focus on practical implementation. General Details: Duration: 1h 9m Updated: 03/2025 Language: English Source: [Hidden Content] Instructor: [Hidden Content] MP4 | Video: AVC, 1920x1080p | Audio: AAC, 44.100 KHz, 2 Ch [Hidden Content]

Can't express my condolence, my heart melting, may he Rest in peace, we lost a good friend and greater personality, my deepest sympathy to his family

Dometrain - Deep Dive: C# Deep dive into the C# programming language Picking up where he left off on the Getting Started with C# course, Microsoft Principal Software Engineering Manager Nick Cosentino will dive deeper into C#'s feature set and explain more advanced features and patterns. This course covers features such as object-oriented programming with C#, with sections on inheritance and composition, low-level streams, advanced methods and functions like callbacks and delegates, and explaining multithreading and asynchronous programming. If you understand the basics of C# and want to gain even more in-depth knowledge of the language, then this course is for you. General Details: Duration: 6h 28m 7s Updated: 02/2025 Language: English Source: [Hidden Content] MP4 | Video: AVC, 1920x1080p | Audio: AAC, 44.100 KHz, 2 Ch | 38 Lectures [Hidden Content]

Anja Garcia - Inferno Workout Program If you're looking for a challenge, this plan is for you. This program was created by our most popular trainer, Anja Garcia. Test your grit, push your limits—then surpass them. Get ready to level up. WHAT TO EXPECT • 6 classes a week for 4 weeks • HIIT, metabolic conditioning, tabata, AMRAPs. • Torch calories, build strength, improve cardio. INTENSITY LEVEL This program is designed for Advanced exercisers. WHAT TO KNOW Check out the 4-week Training Calendar for guidance. The file can be downloaded to your phone or computer. You can click the titles of all the workouts, and it will directly take you to the video. You can also use the calendar as a check form, so you can easily mark off each workout as you complete them. Don't forget to tag @sweatfactor so we can see you working on working out! General Details: Duration: 6h 20m 9s Updated: 02/2025 Language: English Source: [Hidden Content] MP4 | Video: AVC, 1280x720p | Audio: AAC, 48.000 KHz, 2 Ch [Hidden Content]

LinkedIn Learning - Azure AI for Developers Building AI Agents Course details Get up to speed with AI agents in Azure AI. This course is designed for IT professionals with a working knowledge of Azure, GitHub, and Python who are looking to build AI agents using Azure OpenAI. Instructor Ziggy Zulueta offers a deep dive into creating agents with Azure OpenAI and Python using different frameworks such as the OpenAI Assistants API, Semantic Kernel, and AutoGen. This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time—all while using a tool that you’ll likely encounter in the workplace. Skills you’ll gain - AI Agents - Semantic Kernel - OpenAI Products General Details: Duration: 1h 53m Updated: 02/2025 Language: English Subtitle: .SRT Included Source: [Hidden Content] MP4 | Video: AVC, 1280x720p | Audio: AAC, 44.100 KHz, 2 Ch | 29 Lectures [Hidden Content]

Let it go and leave it please, he said, it got done in error might be the situation confused him, so, that's not a big deal, you can add that comment again if it's that necessary, and I'm sure he won't trash anything that doesn't supposed to be wiped unless anything goes against the rules. Yup, that what I concerned for, the time they have taken already, it could've sorted until now, Not sure what making it hard for them to fix it, I know it can be anything but at least any of the owners can make heads up or something, just wondering, anyway, willing to see it up. Let's see how far it goes

Coursera - Advanced Backup Management and Recovery Scenarios Build your subject-matter expertise This course is part of the Oracle Database Backup and Recovery Using RMAN Specialization When you enroll in this course, you'll also be enrolled in this Specialization. - Learn new concepts from industry experts - Gain a foundational understanding of a subject or tool - Develop job-relevant skills with hands-on projects - Earn a shareable career certificate What you'll learn - Master advanced RMAN recovery scenarios, including point-in-time recovery and cross-platform data transport. - Implement secure RMAN backup encryption techniques like dual-mode and transparent encryption. - Optimize backup strategies using RPO, RTO, and modern database backup best practices. - Perform database recovery for critical scenarios such as control file, SPFILE, and redo log losses. There are 6 modules in this course Gain expertise in advanced backup and recovery strategies with this course designed to equip you with critical skills. You will learn to manage RMAN recovery catalogs, implement secure encryption methods, optimize backup plans with RPO and RTO strategies, and perform advanced recovery scenarios, including point-in-time recovery (PITR), cross-platform data transport, and handling corrupted blocks. The course begins by delving into the management of RMAN recovery catalogs, teaching you how to create, synchronize, and manage recovery repositories. Next, you’ll explore secure backup methods, including transparent encryption, password-based keystore, and dual-mode encryption, ensuring your backups remain robust and secure. As you progress, you'll learn best practices for database backups, including how to define effective Recovery Point Objectives (RPO) and Recovery Time Objectives (RTO). Advanced recovery techniques will also be covered, such as point-in-time recovery (PITR), restoring control files and server parameter files (SPFILE), and handling redo log losses. Designed for database administrators and IT professionals, this course is ideal for those with prior RMAN and database management experience. Its advanced focus provides valuable insights and hands-on experience to tackle even the most complex database recovery challenges. Instructor Packt - Course Instructors Offered by Packt General Details: Duration: 9h 8m 32s Updated: 02/2025 Language: English Source: [Hidden Content] MP4 | Video: AVC, 1920x1080p | Audio: AAC, 44.100 KHz, 2 Ch | 37 Files, 6 Folders | 33 Lectures [Hidden Content]

Just curious, did you hear anything from them so far? Or they just left all of us without sorting it up? I believe, you might be thinking the same, where have they gone?

MasterClass - Will Wright Teaches Game Design and Theory Collaboration, prototyping, playtesting. The Sims creator Will Wright breaks down his process for designing games that unleash player creativity. Learn the art and science of game design with Will Wright, the mind behind SimCity and The Sims. In this game design class, Will teaches you how to create games that empower players and unleash their imagination. You’ll develop a tool set for understanding player psychology, as well as learn Will’s approach to generating and pitching ideas, prototyping, playtesting, and building a community. Instructor(s): Will Wright Class Length: (4 hours 16 minutes) Category: Art & Design, Games & Digital Media, Science & Technology, Writing Topics Covered: - Explore Advanced Gaming - Learn Worldbuilding & Genre Writing - Paint, Design, or Create Art - Use Behavioral Science to Read Others General Details: Duration: 4h 16m 28s (21 video lessons) Updated: 02/2025 Language: English Source: [Hidden Content] MP4 | Video: AVC, 1280x720p | Audio: AAC, 48.000 Khz, 2 Ch | 39 Files | 17 PDF included | 21 Lectures [Hidden Content]

LinkedIn Learning - Running Jenkins on AWS Course details Learn how to create and move a master instance of Jenkins to the cloud-based servers of AWS (Amazon Web Services). In this course, instructor Michael Jenkins covers steps for setting up Jenkins, creating a build environment, connecting with webhooks, using a deployment service, and shutting down AWS resources. First, Michael shows you how to create a master instance of Jenkins, including how to configure a security group, a NGINX reverse proxy, and your Jenkins master instance. Next, he steps through creating a build environment and connect the Jenkins master server to the build server. Michael explains what a webhook is and how you can create and test one. He goes over how to deploy using Elastic Beanstalk. Finally, Michael discusses how to stop or remove AWS resources. What’s included Practice while you learn - 1 exercise file Test your knowledge - 5 quizzes Skills you’ll gain - Jenkins - Amazon Web Services (AWS) General Details: Duration: 2h 8m 38s Updated: 02/2025 Language: English Subtitle: .SRT English Source: [Hidden Content] MP4 | Video: AVC, 1280x720p | Audio: AAC, 48.00 KHz, 2 Ch | 35 Lectures | 71 Files, 7 Folders [Hidden Content]

Domestika - Specialization In Graphic Design And Visual Communication [2025] Master's in Graphic Design: Master color, composition, and visual perception to create impactful and coherent visual identities. Discover the fascinating world of graphic design and master its fundamental concepts with this program designed by Silvia Ferpal, Leire Fernández, Eduardo Herrera, Javier Alcaraz, Esteban Ibarra and Enric Jardí. Immerse yourself in the artistic and cultural influences that have shaped design over time, while exploring the laws of visual perception to create dynamic and balanced compositions. Learn to develop your own visual universe using geometric shapes, typography and color to effectively communicate visual messages. As you progress, explore the importance of color in design and its emotional impact. Learn how to apply harmony, contrast, and functional color classifications to enhance your projects. Gain key skills in composition techniques, balance, movement, and iconography. Finally, apply what you’ve learned to personal projects, creating coherent and lasting visual identities. This course offers you the opportunity to transform your creativity into impactful graphic artworks, guided by renowned experts in the field of graphic design. What will you learn in this specialization? - 7 Modules, Taught by 6 selected expert teachers 1. Introduction and inspiration 2. Graphic design for beginners 3. Color applied to graphic design 4. Composition techniques for graphic design 5. The laws of visual perception: unity, weight, balance and movement 6. Graphic design from simple geometries 7. How to think like a graphic designer What is this course's project? You will design a series of images that express your visual universe in template format for Instagram. You will explore key concepts such as shape, typography, color and composition to develop a striking visual project based on your imagination and creativity. Who is this specialization for? This course is ideal for aspiring graphic designers, art students, self-taught creatives, and professionals who wish to strengthen their design skills. Perfect for those looking to master fundamental concepts, explore visual perception, and develop visually striking projects. Requirements and materials No extensive prior knowledge is required. You need access to a computer with basic graphic design software and an internet connection. A notebook for sketching and exploring ideas is also helpful in developing your creativity and visual concepts. General Details: Duration: 7 modules, 107 lessons (19h 21s) Updated: 02/2025 (Haven't updated on source) Language: English Subtitle: .SRT (English) Source: [Hidden Content] MP4 | Video: AVC, 1920x1080p | Audio: AAC, 44.100 KHz, 2 Ch | 214 Files, 7 Folders [Hidden Content]