Znajdź zawartość

Free Download [Ai] Build A Object Recognition App With Python & Angular Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.64 GB | Duration: 3h 1m Develop AI-driven web apps using FastAPI and Angular. Learn Machine Learning with Python for developers. What you'll learn AI and Machine Learning Fundamentals with hands on Basic Programming in Python and Typescript Handle frameworks like FastAPI and Angular Build real world modern object recognition application Requirements No programming experience required. Only computer and access to internet Description [AI] Create a Object Recognition Web App with Python & AngularBuild AI-driven web apps with FastAPI and Angular. Discover Machine Learning with Python for developers.This comprehensive course, "[AI] Create a Object Recognition Web App with Python & Angular," is designed to empower developers with the skills to build cutting-edge AI-powered applications. By combining the power of FastAPI, TensorFlow, and Angular, students will learn to create a full-stack object recognition web app that showcases the potential of machine learning in modern web development.Throughout this hands-on course, parti[beeep]nts will dive deep into both backend and frontend technologies, with a primary focus on Python for AI and backend development, and TypeScript for frontend implementation. The course begins by introducing students to the fundamentals of machine learning and computer vision, providing a solid foundation in AI concepts essential for object recognition tasks.***DISCLAIMER*** This course is part of a 3 applications series where we build the same app with different technologies including Angular, React and a cross platform Mobile App with React Native CLI. Please choose the frontend framework that fits you best.Students will then explore the FastAPI framework, learning how to create efficient and scalable REST APIs that serve as the backbone of the application. This section will cover topics such as request handling, data validation, and asynchronous programming in Python, ensuring that the backend can handle the demands of real-time object recognition processing.The heart of the course lies in its machine learning component, where students will work extensively with TensorFlow to build and train custom object recognition models. Parti[beeep]nts will learn how to prepare datasets, design neural network architectures, and fine-tune pre-trained models for optimal performance. The course will also cover essential topics such as data augmentation, transfer learning, and model evaluation techniques.On the frontend, students will utilize Angular and TypeScript to create a dynamic and responsive user interface. This section will focus on building reusable components, managing application state with services and observables, and implementing real-time updates to display object recognition results. Parti[beeep]nts will also learn how to leverage Angular's powerful features such as dependency injection, routing, and reactive forms to create a robust and scalable frontend application.Throughout the course, emphasis will be placed on best practices in software development, including code organization and project structure. Students will explore Angular's modular architecture and learn how to effectively organize their application into feature modules and shared modules. They will also gain insights into deploying AI-powered web applications, considering factors such as model serving, scalability, and performance optimization.By the end of the course, parti[beeep]nts will have created a fully functional object recognition web app, gaining practical experience in combining AI technologies with modern web development frameworks. This project-based approach ensures that students not only understand the theoretical concepts but also acquire the hands-on skills necessary to build sophisticated AI-driven applications in real-world scenarios.Whether you're a seasoned developer looking to expand your skill set or an AI enthusiast eager to bring machine learning models to life on the web, this course provides the perfect blend of theory and practice to help you achieve your goals in the exciting field of AI-powered web development using Angular and Python.Cover designed by FreePik Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 AI, Machine Learning and Deep Learning Lecture 3 Convulent Neural Networks (CNNs) Lecture 4 Installing VSCode Lecture 5 VSCode Extensions Lecture 6 Best way to take advantage of this course Section 2: FastAPI and Python Setup Lecture 7 What is Python and FastAPI? Lecture 8 Installing Python for MacOS Lecture 9 Installing Python for Windows Lecture 10 Installing and running FastAPI Lecture 11 Another Example Route Lecture 12 Running the server with Uvicorn Lecture 13 Installing packages using requirements.txt Section 3: Angular Application Setup Lecture 14 What is Angular and Typescript? Lecture 15 Angular CLI and creating first app Lecture 16 Creating ImageControl Component Lecture 17 First Template and Conditions Lecture 18 Inputs and Continuing Template Section 4: Creating and Setting Prediction Model Lecture 19 Explaining TensorFlow, SSDMobileNet V2 and Coco Dataset Lecture 20 Adding MobileNetV2 SSD and COCO Model DataSet Lecture 21 Loading PreTrained Model Into App Lecture 22 Run Inference Function Lecture 23 Predict Route Lecture 24 Label_Map Lecture 25 Returning Results from Predict Route Lecture 26 Testing our Route Section 5: Adding Server Data to Frontend Lecture 27 Creating Angular Service Lecture 28 Prediction Type Lecture 29 Upload Image Function in Service Lecture 30 Importing Service into Component Lecture 31 Finalizing Template Lecture 32 Provide HTTPClient Lecture 33 OnFile Selected Lecture 34 UploadImage Function Lecture 35 API Key Lecture 36 Handling Image Upload and Errors Lecture 37 Adding UploadImage to Template and NetworkError Lecture 38 Allow CORS Lecture 39 Testing the Results Section 6: Additional Lectures Lecture 40 Splitting into smaller components Lecture 41 Angular Inputs Lecture 42 Prediction Errors and Mistakes Lecture 43 Use cases and Limitations Section 7: Bonus Lecture 44 Bonus Beginner Python, Frontend and AI developers. Students with interest in how AI works Screenshot Homepage https://www.udemy.com/course/ai-python-angular-object-recognition-app/ Rapidgator https://rg.to/file/1d089f3f7e032bcedad707ebcac33fe7/cktdt.Ai.Build.A.Object.Recognition.App.With.Python..Angular.part1.rar.html https://rg.to/file/ca45ba3c3a0061e388459ae59ea09936/cktdt.Ai.Build.A.Object.Recognition.App.With.Python..Angular.part2.rar.html Fikper Free Download https://fikper.com/GYVHnTqgzC/cktdt.Ai.Build.A.Object.Recognition.App.With.Python..Angular.part1.rar.html https://fikper.com/JX89y96bf2/cktdt.Ai.Build.A.Object.Recognition.App.With.Python..Angular.part2.rar.html No Password - Links are Interchangeable

Free Download [AI] Create a Object Recognition Web App with Python & React Published 10/2024 Created by Alex Softman MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 40 Lectures ( 2h 58m ) | Size: 1.47 GB Build AI-driven web apps with FastAPI and React. Discover Machine Learning with Python for developers. What you'll learn AI and Machine Learning Fundamentals with hands on Basic Programming in Python and Typescript Handle frameworks like FastAPI and React Build real world modern object recognition application Requirements No programming experience required. Only computer and access to internet Description [AI] Create a Object Recognition Web App with Python & ReactBuild AI-driven web apps with FastAPI and React. Discover Machine Learning with Python for developers.This comprehensive course, "[AI] Create a Object Recognition Web App with Python & React," is designed to empower developers with the skills to build cutting-edge AI-powered applications. By combining the power of FastAPI, TensorFlow, and React, students will learn to create a full-stack object recognition web app that showcases the potential of machine learning in modern web development.Throughout this hands-on course, parti[beeep]nts will dive deep into both backend and frontend technologies, with a primary focus on Python for AI and backend development, and TypeScript for frontend implementation. The course begins by introducing students to the fundamentals of machine learning and computer vision, providing a solid foundation in AI concepts essential for object recognition tasks.Students will then explore the FastAPI framework, learning how to create efficient and scalable REST APIs that serve as the backbone of the application. This section will cover topics such as request handling, data validation, and asynchronous programming in Python, ensuring that the backend can handle the demands of real-time object recognition processing.The heart of the course lies in its machine learning component, where students will work extensively with TensorFlow to build and train custom object recognition models. Parti[beeep]nts will learn how to prepare datasets, design neural network architectures, and fine-tune pre-trained models for optimal performance. The course will also cover essential topics such as data augmentation, transfer learning, and model evaluation techniques.On the frontend, students will utilize React and TypeScript to create a dynamic and responsive user interface. This section will focus on building reusable components, managing application state, and implementing real-time updates to display object recognition results. Parti[beeep]nts will also learn how to integrate the frontend with the FastAPI backend, ensuring seamless communication between the two layers of the application.Throughout the course, emphasis will be placed on best practices in software development, including code organization and project structure. Students will also gain insights into deploying AI-powered web applications, considering factors such as model serving, scalability, and performance optimization.By the end of the course, parti[beeep]nts will have created a fully functional object recognition web app, gaining practical experience in combining AI technologies with modern web development frameworks. This project-based approach ensures that students not only understand the theoretical concepts but also acquire the hands-on skills necessary to build sophisticated AI-driven applications in real-world scenarios.Whether you're a seasoned developer looking to expand your skill set or an AI enthusiast eager to bring machine learning models to life on the web, this course provides the perfect blend of theory and practice to help you achieve your goals in the exciting field of AI-powered web development.***DISCLAIMER*** This course is part of a 3 applications series where we build the same app with different technologies including Angular, React and a cross platform Mobile App with React Native CLI. Please choose the frontend framework that fits you best.Cover designed by FreePik Who this course is for Beginner Python, Frontend and AI developers. Students with interest in how AI works Homepage https://www.udemy.com/course/create-a-object-recognition-web-app-with-python-react/ Screenshot Rapidgator https://rg.to/file/50ba8a6d87416e2990ee484c2c116998/jiewf.AI.Create.a.Object.Recognition.Web.App.with.Python..React.part2.rar.html https://rg.to/file/8a1525e0b99a894f56db5dc498e72431/jiewf.AI.Create.a.Object.Recognition.Web.App.with.Python..React.part1.rar.html Fikper Free Download https://fikper.com/ei5AIAv0To/jiewf.AI.Create.a.Object.Recognition.Web.App.with.Python..React.part1.rar.html https://fikper.com/f9X49Tba1k/jiewf.AI.Create.a.Object.Recognition.Web.App.with.Python..React.part2.rar.html No Password - Links are Interchangeable

Free Download Deploy Django + AI ML Face Recognition Web App in AWS Last updated 1/2024 Created by G Sudheer,datascience Anywhere,Brightshine Learn MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + srt | Duration: 104 Lectures ( 8h 14m ) | Size: 3.76 GB Develop & Deploy Face Recognition, Facial Emotion using OpenCV, Machine Learning, Django, Database in Python in AWS What you'll learn Deploy Face Recognition Django Web App in AWS and Heroku Cloud Train your own Machine Learning based Face Recognition Model in Python Train own Facial Emotion Recognition using Machine Learning in Python Develop Django Web App using MVT Framework Design SQLlite Database in Django Train Support Vector Machines, Random Forest Model for Face Recognition in Python Debuging error while Deploying in Heroku Interphase Machine Learning Models with MVT Framework Build Ensemble (stacking) Machine Learning Model combining SVM and Random Forest Models in Python Face Detection with Deep Neural Networks OpenCV Essentials for Face Recognition Managing Heroku Cloud Styling Django Web App with Bootstrap Requirements Should be at least beginner to Python Basic knowledge in Machine Learning Understanding HTML, Bootstrap Should know how to install Python Libraries using pip Description Welcome to the AI and ML Enthusiast Course: Building a Face Recognition Web App with Django, Machine Learning, and Cloud Deployment on AWS!Embark on an exciting journey into Artificial Intelligence as we delve into the realms of Computer Vision and Face Recognition within the expansive field of AI and ML. This course is designed to guide you through the entire development process of an end-to-end project, catering to both machine learning and web development enthusiasts.Course Phases:Phase 1: Machine Learning - Face Identity RecognitionImage processing techniques with OpenCVPrerequisites of the course: Python installation and library setupFace Detection using OpenCV and Deep Neural NetworksFeature extraction using deep neural networksTraining machine learning models: logistic regression, support vector machines, random forestCombining models with a Voting Classifier (stacking method)Model selection and hyperparameter tuning for face recognitionPhase 2: Machine Learning - Facial Emotion RecognitionApplication of machine learning techniques from face identity recognitionIntegration of detection and recognition models into a pipelinePhase 3: Django Web App DevelopmentWeb application development in DjangoRendering HTML, CSS, and Bootstrap for the frontendBackend development in Python using the MVT (Models, Views, and Templates) frameworkDesigning a SQLite database for the Django appInterfacing machine learning pipeline models with the MVT frameworkStyling the app using BootstrapPhase 4: Deployment / Production on AWS CloudDeployment of the Django Web App on AWS Elastic BeanstalkUtilizing the AWS Free Tier for 12 monthsAccessing the app globally through a provided URL/domainTroubleshooting and error resolution during deploymentCourse Highlights:In-depth learning of OpenCV for image processingTraining models for Face Recognition and Facial Emotion RecognitionDjango web app development with MVT frameworkIntegration of machine learning models into the web appDeployment on AWS Elastic Beanstalk with a focus on the AWS Free TierIf you aspire to be an AI developer, this course is your gateway to mastering AI and ML concepts while gaining hands-on experience. Don't miss out - start your journey now!See you inside the course! Who this course is for Anyone who want to learn OpenCV project Python Developers curious about Artificial Intelligence Projects Homepage https://www.udemy.com/course/complete-face-recognition-app-machine-learning-django-heroku/ Screenshot Rapidgator https://rg.to/file/1809166f872d0f51924dbe00fbed5672/pkwuk.Deploy.Django..AI.ML.Face.Recognition.Web.App.in.AWS.part3.rar.html https://rg.to/file/4de77a57c72c6a516dbf254a60d91ae4/pkwuk.Deploy.Django..AI.ML.Face.Recognition.Web.App.in.AWS.part1.rar.html https://rg.to/file/babbedda400a6be1aa58c5077462460b/pkwuk.Deploy.Django..AI.ML.Face.Recognition.Web.App.in.AWS.part2.rar.html https://rg.to/file/dc33ed1d3b977a354fd848bf2faeb26d/pkwuk.Deploy.Django..AI.ML.Face.Recognition.Web.App.in.AWS.part4.rar.html Fikper Free Download https://fikper.com/6QpgcDk4av/pkwuk.Deploy.Django..AI.ML.Face.Recognition.Web.App.in.AWS.part3.rar.html https://fikper.com/9DZap1mWwr/pkwuk.Deploy.Django..AI.ML.Face.Recognition.Web.App.in.AWS.part2.rar.html https://fikper.com/9tltxbKQfU/pkwuk.Deploy.Django..AI.ML.Face.Recognition.Web.App.in.AWS.part4.rar.html https://fikper.com/nreTw3pFik/pkwuk.Deploy.Django..AI.ML.Face.Recognition.Web.App.in.AWS.part1.rar.html No Password - Links are Interchangeable

Free Download Mastering Ifrs 15 - Comprehensive Revenue Recognition Guide Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 12.90 GB | Duration: 8h 11m Your one-stop solution for a comprehensive understanding of IFRS-15 Revenue from Contract with Customers What you'll learn Understand the core principles of IFRS 15 and its application to revenue recognition. Learn how to identify and define performance obligations in customer contracts. Gain practical skills in allocating transaction prices to various performance obligations. Master the process of recognizing revenue over time or at a point in time based on contract terms. Requirements There are no specific prerequisites for taking this course. A basic understanding of accounting principles may be helpful but is not required. The course is designed to be accessible to learners at all levels, including beginners who are looking to deepen their knowledge of IFRS 15 and revenue recognition. Description This course offers a comprehensive understanding of IFRS 15, focusing on revenue recognition and contract management. Whether you're a finance professional, auditor, or a student looking to strengthen your accounting knowledge, this course will provide you with the necessary tools to navigate the complexities of revenue recognition.Through clear explanations and practical examples, you'll learn how to identify performance obligations, allocate transaction prices, and recognize revenue in line with IFRS 15 principles. The course will cover real-world scenarios, helping you apply what you learn to real business situations, ensuring you have both theoretical and practical insights.Designed for learners of all experience levels, this course does not require any prior knowledge of IFRS standards, making it accessible to beginners while also offering advanced content for seasoned professionals. Whether you're involved in financial reporting, contract management, or consultancy, this course will help you ensure compliance with IFRS 15 and improve your understanding of revenue-related transactions.By the end of the course, you'll be equipped with the knowledge and skills to confidently apply IFRS 15 in your day-to-day work, enhance your financial reporting accuracy, and better manage customer contracts. Join us to master IFRS 15 and advance your professional skills in revenue recognition. Overview Section 1: Introduction Lecture 1 Introduction Section 2: Step 1 - Identify the Contract with the Customers Lecture 2 Identify the Contract Lecture 3 Combination of Contracts Section 3: Step 2 - Identify the Performance Obligations in the Contract Lecture 4 Identify the Performance Obligation Lecture 5 Concept of Contract Liability, Contract Asset and Contract Receivable Lecture 6 Concept of Contract Cost Section 4: Step 3 - Determine the Transaction Price Lecture 7 Determine the Transaction Price Lecture 8 Variable Consideration Lecture 9 Sale with the Right of Return Lecture 10 Sale Volume Discount Lecture 11 Settlement Discount Lecture 12 Significant Financing Component Lecture 13 Non Cash Consideration Lecture 14 Consideration Payable to Customer Section 5: Step 4 - Allocate the Transaction Price to each Performance Obligation Lecture 15 Allocate the Transaction Price to each Performance Obligations Lecture 16 Allocation of Discount Section 6: Step 5 - Recognize Revenue As and When Each Performance Obligation Is Satisfied Lecture 17 Recognize Revenue As And When Each Performance Obligiation Is Satistied Section 7: Important Concepts Lecture 18 Contract Modification Lecture 19 Prin[beeep]l versus Agent Considerations Lecture 20 Sales Based Royalty Lecture 21 Warranties This course is ideal for accounting and finance professionals, auditors, and students who want to enhance their understanding of IFRS 15 and its application to revenue recognition. It is also valuable for business owners, managers, and consultants who are involved in financial reporting and contract management. Whether you are a beginner seeking foundational knowledge or an experienced professional looking to refine your expertise, this course is designed to meet your needs. Homepage https://www.udemy.com/course/mastering-ifrs-15-by-murtaza-quaid/ Rapidgator https://rg.to/file/92e3cd9eb795d3f687d0b30e53548fed/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part01.rar.html https://rg.to/file/442a5be47aa333ae8b104536f983fc15/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part02.rar.html https://rg.to/file/f5f433fba6fa1fe0dcd64d093e33be54/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part03.rar.html https://rg.to/file/5741f117e960cb583815c165b16713c3/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part04.rar.html https://rg.to/file/e7d0a60dba75f7e0535b581b45cdf4fc/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part05.rar.html https://rg.to/file/72504505a04e0bd4655e6e8e53f44c0e/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part06.rar.html https://rg.to/file/bf72bdd76a5fc371a73ab388f70f60bb/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part07.rar.html https://rg.to/file/4a867c311a21d0e7d137fda71e07b951/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part08.rar.html https://rg.to/file/253eb8f0b1a488e9a31ad368a653eeef/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part09.rar.html https://rg.to/file/00aaf820c09dd96cdae583c94eeb8db1/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part10.rar.html https://rg.to/file/08ec3cbf10a8b97272b1d610c5c56bf4/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part11.rar.html https://rg.to/file/944283a6134f8cfc1ef16cf7ce72bfbc/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part12.rar.html https://rg.to/file/ab46d985013fd5fd6e9180be35bceb8a/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part13.rar.html https://rg.to/file/616d9c1463a2cf7774efe8d4057b3c33/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part14.rar.html Fikper Free Download https://fikper.com/R6G3DDzP1u/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part01.rar.html https://fikper.com/xEFqO1fGDU/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part02.rar.html https://fikper.com/H9U4NIrFTY/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part03.rar.html https://fikper.com/i517uaeUhe/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part04.rar.html https://fikper.com/YUFvsWNj0I/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part05.rar.html https://fikper.com/beyNQNtbJd/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part06.rar.html https://fikper.com/63EZi8YFNp/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part07.rar.html https://fikper.com/TY8W0cTMF9/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part08.rar.html https://fikper.com/E8ODrV0po8/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part09.rar.html https://fikper.com/Ce9F0FfJBx/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part10.rar.html https://fikper.com/gHyHjeotes/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part11.rar.html https://fikper.com/MKk343IMI7/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part12.rar.html https://fikper.com/MZ1QIHKdv6/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part13.rar.html https://fikper.com/ggpsMH49jd/ffwqx.Mastering.Ifrs.15.Comprehensive.Revenue.Recognition.Guide.part14.rar.html No Password - Links are Interchangeable

epub | 14.32 MB | English | Isbn:9780443289606 | Author: Qiguang Miao PhD, Yunan Li PhD, Xiangzeng Liu PhD, Ruyi Liu PhD | Year: 2024 About ebook: Gesture Recognition: Theory and Applications https://rapidgator.net/file/d1d450ead58b8ea4b757615edf521fa0/ https://nitroflare.com/view/556E8BE59F3FEC7/

Running a Profitable Business: Revenue Recognition With Jim and Kay Stice Size: 596MB | Duration: 1h 32m | Video: AVC (.mp4) 1280x720 30fps | Audio: AAC 48KHz 2ch Genre: eLearning | Level: Appropriate for all | Language: English Revenue recognition determines when a sale should be recorded: This month or next month? This year or next year? This seems like an easy question until you consider situations in which a company sells a package of goods and services for one joint price, aka multi-element transactions. But without recognizing revenue, a company can't hope to report any profit. Accordingly, company management is typically under great pressure to recognize revenue as soon as possible. Want to understand these concepts better? Join professors Jim and Kay Stice as they introduce the theory, practice, and implications of revenue recognition. Together they demonstrate how this seemingly innocent accounting topic can turn a reported profit into a reported loss, sometimes with multibillion dollar implications for company values. Learn more about basic accounting practices in Jim and Kay's Accounting Fundamentals course. Topics include: * Defining revenue recognition * Timing revenue recognition * Understanding multi-element transactions * Valuing companies * Reviewing the great revenue frauds and scandals of history Download From NitroFlare http://www.nitroflare.com/view/A7CD41891782349/xidau123_LcRunProfitBusRevenueRecogn.rar Download From Rapidgator http://rapidgator.net/file/b7564310762e986125abb7a67586f32f/xidau123_LcRunProfitBusRevenueRecogn.rar.html

Pluralsight - Optical Character Recognition with Windows Runtime English | 2h 23m | AVC (.mp4) 1024x768 15fps | AAC 48KHz 2ch | 438 Mb Genre: eLearning This course gives a comprehensive introduction to the Windows Runtime Optical Character Recognition library as well as a general introduction to Optical Character Recognition. We also cover integration with speech synthesis, translation, pattern matching, and share. DOWNLOAD http://rapidgator.net/file/6c35f574be105da6ff4b2ab2d2aa1b30/Optical.part1.rar.html http://rapidgator.net/file/cf578606700df362d50a8f0f5d5673af/Optical.part2.rar.html http://rapidgator.net/file/4e5a4edf0c09e73d8e09432241086bd9/Optical.part3.rar.html http://rapidgator.net/file/a67ef24868dda555d00d3da3eb8bf426/Optical.part4.rar.html http://rapidgator.net/file/a5725716f79fcf247ba4a1bf1d2dff2e/Optical.part5.rar.html http://uploaded.net/file/ykwj8lg1/Optical.part1.rar http://uploaded.net/file/ncf0usnm/Optical.part2.rar http://uploaded.net/file/z3415ief/Optical.part3.rar http://uploaded.net/file/n5zfobxm/Optical.part4.rar http://uploaded.net/file/ob4dkv8k/Optical.part5.rar http://www.uploadable.ch/file/daGtb4vHTSjM/Optical.part1.rar http://www.uploadable.ch/file/jxGMXQvGF7gc/Optical.part2.rar http://www.uploadable.ch/file/vjGXhZMTy7TV/Optical.part3.rar http://www.uploadable.ch/file/QuNGU83cp8Mv/Optical.part4.rar http://www.uploadable.ch/file/bThePUgACbqk/Optical.part5.rar http://turbobit.net/l9d7qu4seuox/Optical.part1.rar.html http://turbobit.net/k607z4btp37e/Optical.part2.rar.html http://turbobit.net/ef0gcu65eojr/Optical.part3.rar.html http://turbobit.net/v71aeh1z77o7/Optical.part4.rar.html http://turbobit.net/w7r6civyyg63/Optical.part5.rar.html

Pluralsight - Optical Character Recognition with Windows Runtime With Iris Classon 946MB | Duration: 2h 23m | Video: AVC (.mp4) 1024x768 15fps | Audio: AAC 48KHz 2ch Genre: eLearning | Level: Intermediate | Language: English This course gives a comprehensive introduction to the Windows Runtime Optical Character Recognition library as well as a general introduction to Optical Character Recognition. We also cover integration with speech synthesis, translation, pattern matching, and share. Download From Uploaded http://uploaded.net/file/zzkyiwnq/xidau123_opticcharacterecogwinruntim.part1.rar http://uploaded.net/file/xw21fwts/xidau123_opticcharacterecogwinruntim.part2.rar http://uploaded.net/file/mlxhipil/xidau123_opticcharacterecogwinruntim.part3.rar Download From NitroFlare http://www.nitroflare.com/view/B26963AA1C86013/xidau123_opticcharacterecogwinruntim.part1.rar http://www.nitroflare.com/view/5828E9B863FB847/xidau123_opticcharacterecogwinruntim.part2.rar http://www.nitroflare.com/view/5A0E5D6415B17F0/xidau123_opticcharacterecogwinruntim.part3.rar Download From Rapidgator http://rapidgator.net/file/e65002c0293f070f6768c7514d0dbf56/xidau123_opticcharacterecogwinruntim.part1.rar.html http://rapidgator.net/file/e8b9fd04f705eacb1e25f63bb87ac7b3/xidau123_opticcharacterecogwinruntim.part2.rar.html http://rapidgator.net/file/1f81601a170c596f359d3301d9b935fc/xidau123_opticcharacterecogwinruntim.part3.rar.html Download From Uploadable http://www.uploadable.ch/file/5rhDpNsKBPEj/xidau123_opticcharacterecogwinruntim.part1.rar http://www.uploadable.ch/file/2AZ8NhvbhP3N/xidau123_opticcharacterecogwinruntim.part2.rar http://www.uploadable.ch/file/TVJarHATazsG/xidau123_opticcharacterecogwinruntim.part3.rar