O documento apresenta uma introdu??o ao Git e ao GitHub, incluindo: (1) os conceitos de controle de vers?o e as vantagens do controle de vers?o distribu¨ªdo em rela??o aos outros m¨¦todos; (2) um tutorial pr¨¢tico sobre como usar os principais comandos do Git localmente; e (3) como publicar um reposit¨®rio no GitHub e sincroniz¨¢-lo com o reposit¨®rio local.
The release of TensorFlow 2.0 comes with a significant number of improvements over its 1.x version, all with a focus on ease of usability and a better user experience. We will give an overview of what TensorFlow 2.0 is and discuss how to get started building models from scratch using TensorFlow 2.0¡¯s high-level api, Keras. We will walk through an example step-by-step in Python of how to build an image classifier. We will then showcase how to leverage a transfer learning to make building a model even easier! With transfer learning, we can leverage other pretrained models such as ImageNet to drastically speed up the training time of our model. TensorFlow 2.0 makes this incredibly simple to do.
Git init creates a .git repository in a project directory to track changes over time, building a history. The .git directory contains files like HEAD, config, and objects that store metadata and data for the local repository. Git add stages files, git commit commits the staged files to the local repository, and git status shows file status. Remote repositories on services like GitHub can be created and the local repository connected to it with git remote add and git push to push local commits remotely. Branches allow parallel development and are created, switched between, merged, and deleted.
This document provides an overview of version control and Git. It discusses what version control is, why it is used, and common types including local, centralized, and distributed. It then focuses on Git, covering its history and origins from Linux kernel development. Key Git concepts are explained like data storage, file lifecycles, basic commands like clone, add, commit, branch, merge, and working with remotes. Tips are provided on installation, ignoring files, using with IDEs, and further learning resources.
The document is a presentation about TensorFlow. It begins with an introduction that defines machine learning and deep learning. It then discusses what TensorFlow is, including that it is an open-source library for deep learning and ML, was developed by Google Brain, and uses data flow graphs to represent computations. The presentation explains benefits of TensorFlow like parallelism, distributed execution, and portability. It provides examples of companies using TensorFlow and demonstrates cool projects that can be built with it, like image classification, object detection, and speech recognition. Finally, it concludes that TensorFlow is helping achieve amazing advancements in machine learning.
Git is a version control system that allows developers to work together and track changes to files over time. GitHub is a web-based platform that uses Git version control and allows collaboration on projects. The speakers demonstrated how to set up Git locally, create a GitHub account, initialize and push a repository, make commits, create branches, pull and push changes, fork repositories, and make pull requests to contribute code back to the original project. Open source development was discussed, including competitions that promote contributions to open source projects.
SciPy22 - Building binary extensions with pybind11, scikit build, and cibuild...Henry Schreiner
?
Building binary extensions is easier than ever thanks to several key libraries. Pybind11 provides a natural C++ language for extensions without requiring pre-processing or special dependencies. Scikit-build ties the premier C++ build system, CMake, into the Python extension build process. And cibuildwheel makes it easy to build highly compatible wheels for over 80 different platforms using CI or on your local machine. We will look at advancements to all three libraries over the last year, as well as future plans.
The document discusses object-oriented programming concepts in Python including classes, objects, methods, encapsulation, inheritance, and polymorphism. It provides examples of defining a class with attributes and methods, instantiating objects from a class, and accessing object attributes and methods. It also covers the differences between procedure-oriented and object-oriented programming, and fundamental OOP concepts like encapsulation, inheritance, and polymorphism in Python.
The document provides an overview of key concepts in C++, including:
1) C++ adds object-oriented programming capabilities to C while maintaining C's power and flexibility. It was created in 1979 to provide object-oriented programming features to C.
2) Object-oriented programming encourages breaking problems into constituent parts called objects that contain related instructions and data. The three main traits of OOP are encapsulation, polymorphism, and inheritance.
3) C++ supports both traditional and modern styles, with newer headers placed in the std namespace. Keywords like class, public, and virtual allow defining classes and controlling access to members. Functions can be overloaded if their signatures differ.
Installing Anaconda Distribution of PythonJatin Miglani
?
This document provides an overview of Anaconda, how it differs from a standard Python distribution, and how to install and use it. Anaconda is an open-source distribution of Python and R that includes over 1,000 data science packages to simplify package management. It uses the conda package manager to handle environments and installation of packages from various repositories. The document outlines how to install Anaconda, use conda commands to manage packages and environments, and integrate Anaconda with the PyCharm IDE.
The document is a presentation about TensorFlow. It begins with an introduction that defines machine learning and deep learning. It then discusses what TensorFlow is, including that it is an open-source library for deep learning and ML, was developed by Google Brain, and uses data flow graphs to represent computations. The presentation explains benefits of TensorFlow like parallelism, distributed execution, and portability. It provides examples of companies using TensorFlow and demonstrates cool projects that can be built with it, like image classification, object detection, and speech recognition. Finally, it concludes that TensorFlow is helping achieve amazing advancements in machine learning.
Git is a version control system that allows developers to work together and track changes to files over time. GitHub is a web-based platform that uses Git version control and allows collaboration on projects. The speakers demonstrated how to set up Git locally, create a GitHub account, initialize and push a repository, make commits, create branches, pull and push changes, fork repositories, and make pull requests to contribute code back to the original project. Open source development was discussed, including competitions that promote contributions to open source projects.
SciPy22 - Building binary extensions with pybind11, scikit build, and cibuild...Henry Schreiner
?
Building binary extensions is easier than ever thanks to several key libraries. Pybind11 provides a natural C++ language for extensions without requiring pre-processing or special dependencies. Scikit-build ties the premier C++ build system, CMake, into the Python extension build process. And cibuildwheel makes it easy to build highly compatible wheels for over 80 different platforms using CI or on your local machine. We will look at advancements to all three libraries over the last year, as well as future plans.
The document discusses object-oriented programming concepts in Python including classes, objects, methods, encapsulation, inheritance, and polymorphism. It provides examples of defining a class with attributes and methods, instantiating objects from a class, and accessing object attributes and methods. It also covers the differences between procedure-oriented and object-oriented programming, and fundamental OOP concepts like encapsulation, inheritance, and polymorphism in Python.
The document provides an overview of key concepts in C++, including:
1) C++ adds object-oriented programming capabilities to C while maintaining C's power and flexibility. It was created in 1979 to provide object-oriented programming features to C.
2) Object-oriented programming encourages breaking problems into constituent parts called objects that contain related instructions and data. The three main traits of OOP are encapsulation, polymorphism, and inheritance.
3) C++ supports both traditional and modern styles, with newer headers placed in the std namespace. Keywords like class, public, and virtual allow defining classes and controlling access to members. Functions can be overloaded if their signatures differ.
Installing Anaconda Distribution of PythonJatin Miglani
?
This document provides an overview of Anaconda, how it differs from a standard Python distribution, and how to install and use it. Anaconda is an open-source distribution of Python and R that includes over 1,000 data science packages to simplify package management. It uses the conda package manager to handle environments and installation of packages from various repositories. The document outlines how to install Anaconda, use conda commands to manage packages and environments, and integrate Anaconda with the PyCharm IDE.
- Microsoft Azure and cloud trends introduction. Azure is an innovative set of cloud services that go beyond infrastructure.
- The presenter Ian Choi introduces himself and his background which includes being a Microsoft manager and community contributions to open source projects.
- The presentation covers an introduction to Microsoft Azure cloud, cloud and serverless trends, 5 tips for quick Azure adoption, and conclusions.
OpenStack I18n Product Update at Shanghai: how OpenStack translation started ...Ian Choi
?
This is one of OpenStack project team updates and covers the latest changes in I18n project including the background on how OpenStack translation started from Chinese language team.
Actual speaker: Frank and Ian
[OpenInfra Days Vietnam 2019] Innovation with open sources and app modernizat...Ian Choi
?
This document discusses innovation and application modernization using open source tools like Kubernetes and containers. It begins by outlining the challenges of migrating applications to the cloud and describes different approaches from simply redeploying applications to fully rearchitecting them. It then discusses how open source tools like Kubernetes and containers can help with application modernization approaches like lift and shift, microservices, machine learning, and IoT solutions. Specific capabilities and scenarios are provided for each along with examples. The document closes by discussing Microsoft's contributions to open source projects in the Kubernetes and container ecosystem.