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Free Download Pluralsight - Real-time Stream Processing with PySpark Released 4/2025 By Ivan Gavryliuk MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 4m | Size: 112 MB Apache Spark is the most widely used analytics engine for large-scale data processing. This course will teach you how to process real-time data streams and productionize real-time data applications. Handling real-time data streams is crucial for modern applications, but many find it challenging to process and analyze data efficiently as it arrives. In this course, Real-time Stream Processing with PySpark, you'll gain the ability to build and deploy scalable, real-time data applications using Apache Spark and Python. First, you'll explore the fundamentals of the modern Spark Streaming and structured streaming concepts. Next, you'll discover advanced streaming techniques, such as window operations, stateful transformations, and fault tolerance, to enhance the reliability and performance of your applications. Finally, you'll learn how to integrate PySpark with various data sources and sinks, enabling seamless data ingestion and output to and from your streaming applications. When you're finished with this course, you'll have the skills and knowledge of stream processing with PySpark needed to develop robust, real-time data processing systems that can handle large-scale data streams efficiently. Homepage: https://app.pluralsight.com/library/courses/pyspark-real-time-stream-processing/table-of-contents [b]AusFile[/b] https://ausfile.com/ogrqyy0ruok7/rmdek.Pluralsight..Realtime.Stream.Processing.with.PySpark.rar.html Fileaxa https://fileaxa.com/8ri6egcizpif/rmdek.Pluralsight..Realtime.Stream.Processing.with.PySpark.rar TakeFile https://takefile.link/0yde06e89z0d/rmdek.Pluralsight..Realtime.Stream.Processing.with.PySpark.rar.html Rapidgator http://peeplink.in/3c17aa9443ea Fikper Free Download https://fikper.com/C0EB9vLrpu/rmdek.Pluralsight..Realtime.Stream.Processing.with.PySpark.rar.html No Password - Links are Interchangeable

In the Shadow of Kings: (A Time of Dragons: Book 2) (The Time of Dragons) - [AUDIOBOOK] m4b | 744.5 MB | Author: Quaintrell, Philip C | Year: 2024 Description: Category:Comic and Graphic Books, Fantasy, Fiction Download Link: DDownload AusFile https://ausfile.com/c5ua35fm6gkd RapidGator https://rapidgator.net/file/e2d723d4450adede4b1df2624c3438ee/ https://ddownload.com/m10dywgauhky

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Free Download Udemy - Speed Time and Distance Last updated: 3/2021 Created by: Srinivasa Rao Gorantla MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 44 Lectures ( 5h 29m ) | Size: 1.72 GB Basics and Shortcuts - Speed Time and Distance What you'll learn Speed, Time, and Distance is a very important topic for all entrance exams like GRE/GMAT/CAT , for competitive exams like Bank P.O, and other recruitment exams. Students learn all the concepts required for the above said exams Students learn short cuts to solve the questions in quick time Students will be able to practice questions. Requirements Since I am covering the topic right from the basics, there are no prerequisites. Description Speed Time and Distance is a very important topic for all entrance exams like GRE/GMAT/CAT/XAT/NMAT and also for competitive exams like Bank P.O, SSC and other recruitment exams.• This course is divided in to ten sections.1. Basic ConceptsThe entire topic of Speed Time and Distance depends on the basic relation/ratio between Speed and Time, Time and Distance, Speed and Time. These ratios are discussed in this section.2. Average SpeedThe special cases of average speed and the short cuts, formulae to solve such questions are discussed in detail.3. Relative SpeedThe relative speed when two objects move in the same direction and opposite direction and related concepts are discussed in this section.4.Meeting PointWhere do two persons meet, when they start from the same end and opposite ends and related concepts are dealt in detail.5.TrainsThe concepts and questions on trains are discussed.6.Linear RacesThe concepts and key points on linear races are discussed in this section.7.Circular TracksThe important points on circular tracks/races are covered in this section.8.ClocksHow to find the angle between the hands of a clock and related concepts are discussed.9.Boats and streams, EscalatorsThe effective speed when a boat travels in a river and a person moving on an escalator are discussed.10.Time ZonesWhen an aircraft travels between two cities which are in different time zones, the actual travel time and related concepts are discussed. Who this course is for Students appearing for any test with quantitative aptitude, especially exams like GRE, GMAT, CAT and other B-School entrances, and students appearing for SSC, Bank PO, and other similar exams will benefit from this course. Homepage: https://www.udemy.com/course/speed-time-and-distance/ [b]AusFile[/b] https://ausfile.com/0oiscw94b7k7/uuwig.Speed.Time.and.Distance.part1.rar.html https://ausfile.com/rbzczzz331ag/uuwig.Speed.Time.and.Distance.part2.rar.html Rapidgator https://rg.to/file/54b3ebbb7496ff66ce6dca1a7c70ff21/uuwig.Speed.Time.and.Distance.part1.rar.html https://rg.to/file/4c6eee03b6725801a181ba3199d61627/uuwig.Speed.Time.and.Distance.part2.rar.html Fikper Free Download https://fikper.com/6SvomYXma2/uuwig.Speed.Time.and.Distance.part1.rar.html https://fikper.com/xCgsWgObvo/uuwig.Speed.Time.and.Distance.part2.rar.html No Password - Links are Interchangeable

Free Download Udemy - AI PPE Detection Real-Time Workplace Safety with Python&CV Published: 4/2025 Created by: Muhammad Yaqoob G MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 16 Lectures ( 47m ) | Size: 554 MB AI-Powered PPE Detection: Ensuring Workplace Safety in Real Time with Python & Computer Vision What you'll learn Understand the fundamentals of Personal Protective Equipment (PPE) detection and its significance in ensuring workplace safety across various industries. Set up a Python-based development environment with essential libraries, including OpenCV for image processing and Flask for web-based deployment. Explore the YOLOv8 model, optimized for real-time PPE detection in video streams, and apply it to monitor compliance in workplaces using live video feeds. Utilize NVIDIA NIM's Florence 2 model for high-accuracy PPE detection in images, ensuring precise identification of helmets, gloves, vests, masks, and shoes. Learn preprocessing techniques to enhance image and video quality, ensuring compatibility with YOLOv8 and Florence 2 models for optimal detection performance. Visualize PPE detection in real-time by annotating video frames and images with bounding boxes, labels, and confidence scores. Address challenges such as occlusions, variations in PPE visibility, low-light conditions, and motion blur in video-based detection. Develop a real-time monitoring system that enables organizations to ensure worker safety by identifying PPE compliance violations Leverage Flask for deploying a web-based dashboard to display detection results, making it accessible for safety supervisors and administrators. Deploy the system in construction, manufacturing, and other high-risk sites to enhance safety protocols and ensure compliance monitoring. Requirements Basic understanding of Python programming (helpful but not mandatory). A laptop or desktop computer with internet access[Windows OS with Minimum 4GB of RAM). No prior knowledge of AI or Machine Learning is required-this course is beginner-friendly. Enthusiasm to learn and build practical projects using AI and IoT tools. Description Welcome to the AI-Powered PPE Detection System with YOLOv8, NVIDIA NIM, and Flask! In this hands-on course, you'll learn how to build a real-time Personal Protective Equipment (PPE) detection system using YOLOv8 for video-based detection, NVIDIA NIM's Florence 2 model for image-based detection, and Flask for web-based visualization.This course focuses on leveraging deep learning to automatically detect essential safety gear, such as helmets, gloves, vests, masks, and shoes, in workplace environments. By the end of the course, you'll have developed a complete PPE compliance monitoring system, accessible through a Flask-based web dashboard for real-time safety monitoring.What You'll Learn:• Set up your Python development environment and install essential libraries like OpenCV, Flask, YOLOv8, and NVIDIA NIM's Florence 2 for building your system.• Train and deploy a YOLOv8 model to detect PPE items in live video feeds, analyzing worker safety compliance in real time.• Utilize the NVIDIA NIM Florence 2 model for high-accuracy PPE detection in images, ensuring robust workplace safety monitoring.• Preprocess video streams and images to optimize detection accuracy, addressing variations in lighting, occlusions, and movement.• Build a Flask-based web interface to display real-time PPE detection results, making it easy to monitor workplace safety from anywhere.• Explore optimization techniques to improve real-time inference speed and enhance detection accuracy in different environmental conditions.• Develop a complete PPE compliance monitoring system, ideal for construction sites, manufacturing plants, warehouses, and industrial workplaces.By the end of this course, you'll have built a robust AI-powered PPE detection system, equipping you with valuable computer vision, deep learning, and web deployment skills.This course is designed for beginners and intermediate learners who want to develop AI-powered safety monitoring applications. No prior experience with Flask or YOLO models is required, as we will guide you step by step to create a real-world PPE detection system.Enroll today and start building your AI-Powered PPE Detection: Ensuring Workplace Safety in Real Time ! Who this course is for Students looking to explore AI and its practical applications in Personal Protective Equipment (PPE) detection using YOLOv8 and NVIDIA NIM's Florence 2 model. Working professionals aiming to upskill in AI, Machine Learning, and Computer Vision for workplace safety and compliance monitoring. IoT and Safety Tech enthusiasts interested in integrating AI-driven PPE detection into smart monitoring systems for industrial and construction environments. Aspiring developers who want to build a career in AI, machine learning, or computer vision, with a focus on real-world safety solutions. 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Free Download Udemy - A comprehensive course on Time and Work (Work Rate) Last updated: 2/2021 Created by: Srinivasa Rao Gorantla MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 35 Lectures ( 3h 59m ) | Size: 1.32 GB Basics and Shortcuts -Time & Work (Work Rate), Ratio, Proportion, Variation What you'll learn Time & Work (Work Rate) is a very important topic for all entrance exams like GRE/GMAT/CAT, for competitive exams like Bank PO, SSC and other recruitment exams. Students learn all the concepts required for the above said exams Students learn short cuts to solve the questions in quick time Students will be able to practice questions. Requirements Since I am covering the topic right from the basics, there are no prerequisites. Description Time & Work (Work Rate) is a very important topic for all entrance exams like GRE/GMAT/CAT/XAT/NMAT and also for competitive exams like Bank P.O, SSC and other recruitment exams.• In all the exams where quantitative aptitude is a test area, Time & Work(Work Rate) questions are asked invariably.This course is divided in to three parts.1. Ratio, Proportion and Variation Time and work concepts and questions depend on the concepts of Ratio, Proportion and Variation. Hence basic concepts of ratio, proportion and their application are discussed in detail. Different variation concepts like direct variation, inverse variation and joint variation and their application have been discussed in detail. 2. Time & Work (Work Rate). Different approaches to solve Time & Work questions like (i)Unitary method, (ii) L.C.M Method (iii)Efficiency method are explained in detail. Various concepts and questions covering the following cases have been discussed (a) Two or more people working together all the time (b) Two or more people working together partially (c) Two or more people working alternately or on rotation (d) Two or more people sharing the wages paid (e) Variation based questions (f) Pipes and Cisterns3. Practice questions. Applying the concepts learned in the first two modules, a few practice questions have been discussed. Who this course is for Students appearing for any test with quantitative aptitude, especially exams like GRE, GMAT, CAT and other B-School entrances, and students appearing for SSC, Bank PO, and other similar exams will benefit from this course. Homepage: https://www.udemy.com/course/a-comprehensive-course-on-time-and-work-work-rate/ [b]AusFile[/b] https://ausfile.com/7jou5wnf2qin/hxhba.A.comprehensive.course.on.Time.and.Work.Work.Rate.part1.rar.html https://ausfile.com/75i3s9wo1zf7/hxhba.A.comprehensive.course.on.Time.and.Work.Work.Rate.part2.rar.html Rapidgator https://rg.to/file/c9df8ccfefcb52940098dfe79f524afa/hxhba.A.comprehensive.course.on.Time.and.Work.Work.Rate.part1.rar.html https://rg.to/file/090beb99d13f9a35cf85a5f7815c1e3e/hxhba.A.comprehensive.course.on.Time.and.Work.Work.Rate.part2.rar.html Fikper Free Download https://fikper.com/MgecRBYryz/hxhba.A.comprehensive.course.on.Time.and.Work.Work.Rate.part1.rar.html https://fikper.com/wf4geQxioe/hxhba.A.comprehensive.course.on.Time.and.Work.Work.Rate.part2.rar.html No Password - Links are Interchangeable

Free Download Udemy - Time-Series Analysis & Regression Forecasting with Python Published 4/2025 Created by eTech School MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 71 Lectures ( 5h 45m ) | Size: 2 GB Transform raw data into powerful forecasts with Python-learn time-series modeling, regression, real-world forecasting. What you'll learn Time-series concepts, notations, and use cases. Data loading, preprocessing, and feature engineering using Python. Visualizing time-series data for insights. Forecasting using AR, MA, ARIMA, and SARIMA models. Handling seasonality and trend components in data. Performing train-test splits and model validation correctly. Applying linear regression (simple and multiple) for forecasting. Interpreting regression outputs and evaluating model accuracy. Requirements Basic knowledge of Python (variables, loops, basic functions). Familiarity with basic statistics (mean, median, correlation). Some exposure to pandas, matplotlib, or NumPy is helpful but not mandatory. No prior experience with time-series or regression needed. Description Course Introduction:Forecasting is at the heart of modern data science, powering decision-making across finance, retail, healthcare, and beyond. This comprehensive course is your step-by-step guide to mastering time-series analysis and regression-based forecasting using Python. Whether you're a budding data scientist or an analyst aiming to add predictive analytics to your skillset, this course covers everything from basic notations to advanced models like ARIMA and SARIMA. You'll also learn how to prepare data for machine learning, visualize trends, and validate models like a pro.Through hands-on coding in Python, real-world use cases, and expert-led instruction, you'll gain the confidence to build and deploy forecasting models that actually drive impact.Section 1: Foundations of Time-Series Analysis in PythonStart your journey by understanding the fundamentals of time-series data-what makes it unique and why it matters in data science. You'll set up your environment with Anaconda and Jupyter, then dive into data loading, preprocessing, and feature engineering. You'll also learn how to visualize time-dependent patterns, apply transformations, and use basic statistical techniques like moving averages and exponential smoothing. By the end of this section, you'll be well-prepared for building time-aware models.Section 2: Time-Series Forecasting ModelsIn this section, you'll move from theory to practice with key time-series forecasting models. Starting with naive models, you'll progress to Auto-Regression (AR), Moving Average (MA), and ARIMA. Learn how to split time-series data properly, validate predictions using walk-forward validation, and interpret autocorrelation using ACF and PACF plots. You'll wrap up with SARIMA, an advanced seasonal model, and apply it all in Python through hands-on coding.Section 3: Data Preprocessing for Linear RegressionBefore building regression models, you need clean and meaningful data. This section teaches you the essential preprocessing steps required for high-quality regression modeling. You'll work through exploratory data analysis, outlier detection, missing value imputation, seasonality handling, and correlation analysis. You'll also transform variables, create dummy variables, and prepare your dataset for modeling. Each concept is reinforced with Python demos to solidify your understanding.Section 4: Building & Evaluating Regression ModelsFinally, bring your data to life by building regression models in Python. You'll understand how to apply the Ordinary Least Squares (OLS) method, interpret coefficients, and evaluate model performance using R-Squared, F-statistics, and more. You'll build both simple and multiple linear regression models, including handling categorical variables. This section ensures you're confident not only in model creation but also in explaining the results effectively.Course Conclusion:Congratulations! You've now developed the core skills required to perform both time-series forecasting and regression modeling using Python. From building clean datasets to visualizing trends and predicting future values, you're ready to tackle real-world forecasting challenges in any domain. Your ability to transform data into insight will set you apart as a capable and confident data professional. Who this course is for Aspiring data scientists and analysts looking to master forecasting. Business intelligence professionals wanting to enhance reporting with prediction. Students in data science or machine learning programs. Python developers eager to apply coding skills to statistical forecasting. Anyone curious about time-series analysis, regression, or predictive modeling. 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Free Download Udemy - Time Management And Timeboxing In Business, Projects, Agile Published: 4/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 649.66 MB | Duration: 0h 55m Mastering Timeboxing and Time Management: Boosting Productivity and Efficiency in Business, Agile, Projects, Life. What you'll learn Understanding Time Management Setting Clear Goals Planning and Organizing Your Time Overcoming Procrastination Managing Energy, Not Just Time Evaluating and Adjusting Your Time Management Plan Requirements For a better learning experience, we suggest you to use a laptop / mobile phone / pen and paper for taking notes, highlighting important points, and making summaries to reinforce your learning. Description Welcome to course: Time Management and Timeboxing in Business, Projects, Agile by MTF InstituteCourse provided by MTF Institute of Management, Technology and FinanceMTF is the global educational and research institute with HQ at Lisbon, Portugal, focused on business & professional hybrid (on-campus and online) education at areas: Business & Administration, Science & Technology, Banking & Finance. MTF R&D center focused on research activities at areas: Artificial Intelligence, Machine Learning, Data Science, Big Data, WEB3, Blockchain, Cryptocurrency & Digital Assets, Metaverses, Digital Transformation, Fintech, Electronic Commerce, Internet of Things. MTF is the official partner of: IBM, Intel, Microsoft, member of the Portuguese Chamber of Commerce and Industry.MTF is present in 216 countries and has been chosen by more than 740 000 students.Course Authors:Join our new course from globally recognized experts: Barbara Gutsch (15+ years of international experience in banking and finance, incl. 7+ years in Swiss private banking as risk and compliance manager) and Olga Margolin (17+ years in Swiss private banking industry, as top executive and business owner, managing international client relationships).Topic Overview:Time Management:This is the process of planning and controlling how you spend your time. Effective time management enables you to work smarter-not harder-so you get more done in less time, even when time is tight and pressures are high.It involves prioritizing tasks, setting goals, and using strategies to increase productivity.Timeboxing:This is a specific time management technique where you allocate a fixed time period-a "timebox"-to a planned activity.Instead of working on a task until it's finished, you work on it within the set time frame. 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