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Udemy – Introduction to Milvus (Vector Database) Using Python 2024-5 Video Tutorial Course Introduction to Milvus (Vector Database) Using Python, Download course Introduction to Milvus (Vector Database) Using Python, Download Introduction to Milvus (Vector Database) Using Python, Free download Introduction to Milvus (Vector Database) Using Python, Free Introduction to Milvus (Vector Database) Using Python, Vijay Anand Ramakrishnan Description Course Introduction to Milvus (Vector Database) Using Python. Milos is the world’s first open source vector database that can store, index and search billions of vectors. Vector databases are one of the emerging technologies of the decade that support modern AI tools, and learning Milos to build highly scalable, real-time AI applications can help you advance in your career faster. This course provides you with comprehensive hands-on skills in Milos using its Python SDK (PyMilvus). Before starting, you should have basic knowledge of Python programming, Linux commands, Docker and Docker Compose. After completing this course, you will be able to: Installing and working with Milos using Python Management of collections and indexes in Milos Perform vector search on vectors stored in Milos Managing users and roles in Milos Using Attu, a web-based user interface used to manage Milos Using Milos to build scalable AI applications What you will learn in the Introduction to Milvus (Vector Database) Using Python course Basics of vector databases Introducing Milos and installing Milos Collections, partitions and indexes in Milos PyMilvus – Python SDK for Milos A real world example using Milos Role-based access control in Milos Attu – a user interface based tool for Milos management This course is suitable for people who Data scientists Artificial intelligence engineers Machine learning engineers MLOps Engineers data engineers Anyone motivated to learn and work with a vector database Course specifications Introduction to Milvus (Vector Database) Using Python Publisher: Udemy Lecturer: Vijay Anand Ramakrishnan Training level: beginner to advanced Training duration: 1 hour and 52 minutes Number of courses: 33 Course headings Course prerequisites Python Docker and Docker Compose Basic Linux Commands Course images Sample video of the course [Hidden Content] Installation guide After Extract, view with your favorite Player. Subtitle: English Quality: 720p download link Download file – 336 MB File(s) password: www.downloadly.ir File size 336 MB

Pluralsight – Django Testing 2024-1 Video Tutorial Course Django Testing, Download course Django Testing, Download Django Testing, Free Django Testing, Free download Django Testing, Tom Compagno Description Django Testing course. This course teaches you the key concepts of building and running tests in Django. In the Django Testing course, you’ll learn how to set up, run, and verify various test scenarios. First, you’ll explore the basics of testing and Django’s testing tools. Then, you’ll discover how to build effective tests in a codebase. Finally, you’ll learn how to use Django’s advanced testing tools. After completing this course, you will have the Django testing skills and knowledge needed to adequately cover the code base of a Django project with various types of testing. What you will learn Creating a test environment: How to prepare a suitable environment for running tests. Building Effective Tests: How to write tests that accurately examine the behavior of your code. Test data management and fixtures: How to create and use test data to simulate different conditions. Running tests carefully: How to run tests and review their results. This course is suitable for people who Want to improve the quality of their Django code? They want to ensure that their application works properly. Want to better understand the Django framework. They are interested in developing testable software. Django Testing course specifications Publisher: Pluralsight Instructor: Tom Compagno Education level: Intermediate Training duration: 1 hour 51 minutes Course headings Images of the Django Testing course Sample video of the course [Hidden Content] Installation guide After Extract, view with your favorite Player. Subtitle: None Quality: 1080p download link Download file – 305 MB File(s) password: www.downloadly.ir File size 305 MB

Oreilly – Deep Learning with R, Second Edition, Video Edition 2022-10 Video Tutorial Course Deep Learning with R Second Edition Video Edition, Download course Deep Learning with R Second Edition Video Edition, Download Deep Learning with R Second Edition Video Edition, Francois Chollet, Free Deep Learning with R Second Edition Video Edition, Free download Deep Learning with R Second Edition Video Edition, J.J. Allaire, Sigrid Keydana, Tomasz Kalinowski Description Deep Learning with R course, Second Edition, Video Edition. In this course you will learn: Deep learning from the basics Image classification and image segmentation Time series forecasting Text classification and machine translation Text production, neural style transfer and image production Deep learning has become essential for data scientists, researchers and software developers. The R language APIs for Keras and TensorFlow make deep learning accessible to all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started using R for core DL tasks such as computer vision, natural language processing, and more. What you will learn in this course Image classification and image segmentation Time series forecasting Text classification and machine translation Text production, neural style transfer and image production This course is suitable for people who Have intermediate skills in R. No prior experience with Keras, TensorFlow, or deep learning is necessary. Course details Publisher: Oreilly Instructor: Francois Chollet , Sigrid Keydana , Tomasz Kalinowski , JJ Allaire Training level: beginner to advanced Training duration: 15 hours and 28 minutes Course headings Chapter 1. What is deep learning? Chapter 1. Before deep learning: A brief history of machine learning Chapter 1. Why deep learning? Why now? Chapter 2. The mathematical building blocks of neural networks Chapter 2. Data representations for neural networks Chapter 2. The gears of neural networks: Tensor operations Chapter 2. The engine of neural networks: Gradient-based optimization Chapter 2. Looking back at our first example Chapter 2. Summary Chapter 3. Introduction to Keras and TensorFlow Chapter 3. What’s Keras? Chapter 3. Keras and TensorFlow: A brief history Chapter 3. Python and R interfaces: A brief history Chapter 3. Setting up a deep learning workspace Chapter 3. First steps with TensorFlow Chapter 3. Tensor attributes Chapter 3. Anatomy of a neural network : Understanding core Keras APIs Chapter 3. Summary Chapter 4. Getting started with neural networks: Classification and regression Chapter 4. Classifying newswires: A multiclass classification example Chapter 4. Predicting house prices: A regression example Chapter 4. Summary Chapter 5. Fundamentals of machine learning Chapter 5. Evaluating machine learning models Chapter 5. Improving model fit Chapter 5. Improving generalization Chapter 5. Summary Chapter 6. The universal workflow of machine learning Chapter 6. Develop a model Chapter 6. Deploy the model Chapter 6. Summary Chapter 7. Working with Keras: A deep dive Chapter 7. Different ways to build Keras models Chapter 7. Using built-in training and evaluation loops Chapter 7. Writing your own training and evaluation loops Chapter 7. Summary Chapter 8. Introduction to deep learning for computer vision Chapter 8. Training a convnet from scratch on a small dataset Chapter 8. Leveraging a pretrained model Chapter 8. Summary Chapter 9. Advanced deep learning for computer vision Chapter 9. An image segmentation example Chapter 9. Modern convnet architecture patterns Chapter 9. Interpreting what convnets learn Chapter 9. Summary Chapter 10. Deep learning for time series Chapter 10. A temperature-forecasting example Chapter 10. Understanding recurrent neural networks Chapter 10. Advanced use of recurrent neural networks Chapter 10. Summary Chapter 11. Deep learning for text Chapter 11. Preparing text data Chapter 11. Two approaches for representing groups of words: Sets and sequences Chapter 11. The Transformer architecture Chapter 11. Beyond text classification: Sequence-to-sequence learning Chapter 11. Summary Chapter 12. Generative deep learning Chapter 12. DeepDream Chapter 12. Neural style transfer Chapter 12. Generating images with variational autoencoders Chapter 12. Introduction to generative adversarial networks Chapter 12. Summary Chapter 13. Best practices for the real world Chapter 13. Scaling-up model training Chapter 13. Summary Chapter 14. Conclusions Chapter 14. The limitations of deep learning Chapter 14. Setting the course toward greater generality in AI Chapter 14. Implementing intelligence: The missing ingredients Chapter 14. The future of deep learning Chapter 14. Staying up-to-date in a fast-moving field Chapter 14. Final words Deep Learning with R course images, Second Edition, Video Edition Sample video of the course [Hidden Content] Installation guide After Extract, view with your favorite Player. Subtitle: None Quality: 1080p download link Download part 1 – 1 GB Download part 2 – 817 MB File(s) password: www.downloadly.ir File size 1.8 GB

Pluralsight – React Native with Expo Deep Dive 2024-3 Video Tutorial Course React Native with Expo Deep Dive, Download course React Native with Expo Deep Dive, Download React Native with Expo Deep Dive, Free download React Native with Expo Deep Dive, Free React Native with Expo Deep Dive, Reggie Dawson Description React Native with Expo Deep Dive is a comprehensive course that teaches you how to build powerful mobile apps with React Native using Expo. Building mobile apps with JavaScript can be challenging at first. In addition to the framework you are using, you also need to install the development kit for your desired platform. This course will help you to quickly and easily build complete applications using Expo. What you will learn: Launching and creating a project with Expo: First, you will learn how to launch Expo and create a new project. Creating Routing and Views: Next, you will learn how to enable routing and create different views for your application. Compile and publish the application: Finally, you will learn how to compile the application for publication on the web and mobile devices. Skills needed to build mobile apps with Expo: After completing this course, you will have the skills and knowledge you need to build your own mobile apps. This course is suitable for people who: They are interested in developing mobile applications. Are familiar with JavaScript and React or want to be familiar with them. Looking for an easier way to start mobile app development with React Native? They want to build a complete mobile application from start to finish. React Native with Expo Deep Dive course specifications Publisher: Pluralsight Instructor: Reggie Dawson Training level: beginner to advanced Training duration: 3 hours 9 minutes Course headings Course images Sample video of the course [Hidden Content] Installation guide After Extract, view with your favorite Player. Subtitle: None Quality: 1080p download link Download file – 732 MB File(s) password: www.downloadly.ir File size 732 MB

Pluralsight – Generative AI for Project Managers 2024-6 Video Tutorial Casey Ayers, Course Generative AI for Project Managers, Download course Generative AI for Project Managers, Download Generative AI for Project Managers, Free download Generative AI for Project Managers, Free Generative AI for Project Managers Description Generative AI for Project Managers course. Generative artificial intelligence is rapidly expanding in small and large organizations. Successful project managers must learn how to best use this technology to achieve their goals. This course will help you do just that. This course will help you get to know the various applications of generative artificial intelligence in project management. You will also explore the advantages and disadvantages of using these models to perform project management tasks. In addition, you will learn what kinds of work can best be done with AI tools and how you can act as an advocate for the responsible use of AI in your organization. What you will learn: Examining examples of how project managers use generative artificial intelligence Understanding the advantages and disadvantages of using artificial intelligence models in project management Learning the types of tasks that AI tools can help you with Learn how to advocate for the responsible use of artificial intelligence in your organization This course is suitable for people who: They are project managers or work in the field of project management. Looking for ways to improve the efficiency and effectiveness of their projects. Interested in learning about emerging technologies such as artificial intelligence. They want to learn about the responsible use of artificial intelligence. Generative AI for Project Managers course specifications Publisher: Pluralsight Instructor: Casey Ayers Training level: beginner to advanced Training duration: 1 hour 12 minutes Course headings Course images Sample video of the course [Hidden Content] Installation guide After Extract, view with your favorite Player. Subtitle: None Quality: 1080p download link Download part 1 – 1 GB Download part 2 – 309 MB File(s) password: www.downloadly.ir File size 1.3 GB

Pluralsight – SwiftUI Fundamentals 2024-4 Video Tutorial Andrew Bancroft, Course SwiftUI Fundamentals, Download course SwiftUI Fundamentals, Download SwiftUI Fundamentals, Free download SwiftUI Fundamentals, Free SwiftUI Fundamentals Description SwiftUI Fundamentals course. This course will teach you how to build iOS apps with adaptive user interfaces that work on different devices using Xcode, Swift, and SwiftUI. iOS app development is a valuable and sought-after skill, but if you’ve never developed in the Apple world before, it may look significantly different from what you’re familiar with. In this course, SwiftUI Fundamentals, you’ll quickly get started using Xcode 15, Swift, and SwiftUI, and learn the fundamental skills needed to build great user interfaces for iOS. What you will learn: SwiftUI tools and techniques: You will be introduced to the tools and learn how to use SwiftUI to create single-page apps with adaptive user interfaces that work on different devices. Appearance Customization: You’ll learn how to add your own style to SwiftUI by customizing the appearance. Working with data and navigation: You will learn to work with data-driven controls and understand navigation options for multi-page applications. This course is suitable for people who: Want to start or improve their iOS app development skills. Looking to learn SwiftUI quickly and effectively. They want to create iOS applications with a beautiful and user-friendly interface. SwiftUI Fundamentals course details Publisher: Pluralsight Lecturer: Andrew Bancroft Training level: beginner to advanced Training duration: 3 hours 26 minutes Course headings Course images Sample video of the course [Hidden Content] Installation guide After Extract, view with your favorite Player. Subtitle: None Quality: 1080p download link Download file – 758 MB File(s) password: www.downloadly.ir File size 758 MB