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- Will golang replace python in the future?
- In recent years, with the rapid development of Internet technology and the continuous progress of society, programming languages have been constantly updated, and some emerging programming languages are gradually replacing the status of old programming languages. Among them, golang, as a new generation of high-performance programming language, has become the first choice of many enterprises and developers. Some even think that golang may replace python in the future. As a high-level language with simple syntax and easy to learn, Python has always been a popular programming tool, especially in artificial intelligence, data science, and We
- Golang . flask 742 2023-04-24 16:58:20
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- Which is better, python or JavaScript?
- With the continuous development of the digital age, programming languages are becoming more and more important in the IT industry, and Python and JavaScript are currently popular programming languages. Both languages have their own characteristics and advantages, but which one is better? This article will conduct a comparative analysis of these two languages so that readers can better choose which language is suitable for them to learn and use. 1. Introduction to Python and JavaScript Python is an interactive programming language and is widely used in data analysis, machine learning, artificial intelligence, etc.
- Front-end Q&A . flask 3096 2023-04-24 15:17:42
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- Learn Python Celery and easily complete asynchronous tasks
- While modern web applications are faster and more convenient than ever, there are still many situations where heavy lifting needs to be offloaded to other parts of the system rather than being performed on the main thread. Examples of these situations include the following: Periodic tasks – jobs that are scheduled to run at specific intervals. For example, daily, monthly report generation. Third Party Tools - Applications should return responses quickly to the user rather than waiting for other tasks to complete first. For example, send emails, notifications, communicate update progress to internal tools. Long-running jobs – jobs that perform complex or resource-expensive work and the user needs to wait for the job to complete. For example. DAG workflow, Map-Reduce based tasks, long-running Spa
- Python Tutorial . flask 1734 2023-04-23 15:31:16
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- Customized training of deep learning models using transfer learning techniques
- Translator | Reviewed by Zhu Xianzhong | Sun Shujuan Transfer learning is a type of machine learning. It is a method applied to neural networks that have been trained or pre-trained, and these pre-trained neural networks are made using millions of trained on data points. The most well-known use of this technology currently is to train deep neural networks, as this method has shown good performance in training deep neural networks using less data. In fact, this technique is also useful in the field of data science, because most real-world data usually does not have millions of data points to train a robust deep learning model. Currently, many models exist that are trained using millions of data points and can be used to train complex deep learning neural networks with maximum accuracy.
- AI . flask 1656 2023-04-23 08:13:06
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- How to design a docker management system
- Docker has become an essential tool for modern enterprises, simplifying the packaging, shipping and deployment of applications. However, Docker requires a large number of commands to manage applications, images, and containers. For enterprises managing large-scale Dockerized applications, this can become very tedious and complex. Therefore, designing a powerful Docker management system is crucial. The following aspects need to be considered when designing a Docker management system. 1. Architecture design Docker management system can be divided into multiple modules, usually including We
- Docker . flask 693 2023-04-18 10:35:51
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- Nine super useful Python libraries for data science
- In this article, we will look at some Python libraries for data science tasks other than the more common ones like panda, scikit-learn, and matplotlib. Although libraries like panda and scikit-learn are commonly used in machine learning tasks, it is always beneficial to understand other Python products in this field. 1. Wget Extracting data from the Internet is one of the important tasks of data scientists. Wget is a free utility that can be used to download non-interactive files from the Internet. It supports HTTP, HTTPS and FTP protocols, as well as file inspection through HTTP proxy
- Python Tutorial . flask 994 2023-04-17 09:25:08
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- How to quickly turn your Python code into an API
- When it comes to API development, you may think of DjangoRESTFramework, Flask, and FastAPI. Yes, they can be used to write APIs. However, the framework shared today allows you to convert existing functions into APIs faster. It is Sanic . Introduction to Sanic Sanic[1] is a Python3.7+ web server and web framework designed to improve performance. It allows the use of the async/await syntax added in Python 3.5, which can effectively avoid blocking and improve response speed. Sanic is committed to providing a simple and fast way to create and launch
- Python Tutorial . flask 2091 2023-04-14 18:28:10
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- The best combination for writing Python code on Windows!
- How to do Python development on Windows? Should I use a plain text editor like the masters do, or should I use a more complete IDE? Should I use the built-in command line tool, or do I need to install a new Terminal? This article will show you how to use MS Terminal and VS Code officially maintained by Microsoft to protect Python development. One of the great benefits of using Windows is that it has so many applications, and even a powerful GPU can do other "work" in your free time. However, unlike Linux or macOS, developing on Windows will always encounter many challenges, whether it is file encoding or environment control.
- Python Tutorial . flask 888 2023-04-14 13:31:03
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- Ten useful Python utility libraries, I recommend you try them!
- Why do I like Python? It's an easy-to-learn programming language for beginners, for another reason: the large number of third-party libraries available out of the box, and 230,000 user-contributed packages that make Python truly powerful and popular. In this article, I have selected 10 of the most useful software packages and describe their functions and features. 1. DashDash is a Python library for building web-based applications without JavaScript. Dash is also a user interface library for creating analytical web applications. Those who use Python for data analysis, data mining, visualization, modeling, instrument control, and reporting can get started immediately
- Python Tutorial . flask 2915 2023-04-13 09:43:12
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- ASGI explained: The future of Python web development
- Translator | Reviewed by Li Rui | Sun Shujuan Python web applications have long followed the Web Server Gateway Interface (WSGI) standard, which describes how they communicate with web servers. WSGI, originally introduced in 2003 and updated in 2010, relies only on easy-to-implement features that are natively available in Python 2.2. As a result, WSGI was quickly integrated into all major Python web frameworks and became the cornerstone of Python web development. Fast forward to 2022. Python2 has been deprecated and Python now has native syntax for handling asynchronous operations such as network calls. WSGI and other standards that assume synchronous behavior by default cannot
- Python Tutorial . flask 1563 2023-04-12 22:37:03
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- How to write Python code on Windows? Excellent strategy is coming!
- How to do Python development on Windows? Should I use a plain text editor like the masters do, or should I use a more complete IDE? Should I use the built-in command line tool, or do I need to install a new Terminal? One of the great benefits of using Windows is that it has so many applications, and even a powerful GPU can do other "work" in your free time. However, unlike Linux or macOS, developing on Windows will always encounter many challenges. Whether it is file encoding, environment control or project compilation, there will always be some magical gains during the development process. These are especially prominent for beginners: various dependency errors may occur when we install a certain library,
- Python Tutorial . flask 1848 2023-04-12 22:22:07
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- ChatGPT sharing-How to develop an LLM application
- 1 Background ChatGPT has caused huge shock in the industry. All walks of life are discussing large language models and general artificial intelligence. AI has experienced more than fifty years of development and is now in a critical period of horizontal development of the industrial structure. This change stems from the paradigm shift in the field of NLP, which has evolved from "pre-training + fine-tuning" to "pre-training, prompting, and prediction". In this new model, downstream tasks adapt to the pre-trained model, making a large model suitable for multiple tasks. This change has laid the foundation for the horizontal division of labor in the AI industry. Large language models have become infrastructure. Prompt Engineering companies have emerged one after another, focusing on connecting users and models. The division of labor in the AI industry has initially taken shape, including underlying infrastructure (cloud services
- AI . flask 2475 2023-04-12 21:43:04
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- Use Flask to build Python microservices on Kubernetes
- Microservices follow Domain Driven Design (DDD) and are independent of the development platform. Python microservices are no exception. The object-oriented nature of Python3 makes it easier to model services in terms of DDD. The power of microservices architecture lies in its multilingual nature. The enterprise breaks down its functionality into a set of microservices, and each team is free to choose a platform. Our user management system has been decomposed into four microservices, namely add, find, search and log services. Added services are developed on the Java platform and deployed on Kubernetes clusters for resiliency and scalability. This does not mean that the rest of the services must also be developed in Java. We are free to choose the platform that suits our individual services.
- Python Tutorial . flask 1431 2023-04-12 20:58:12
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- Eight Python libraries to improve data science efficiency!
- 1. OptunaOptuna is an open source hyperparameter optimization framework that can automatically find the best hyperparameters for machine learning models. The most basic (and probably well-known) alternative is sklearn's GridSearchCV, which will try multiple hyperparameter combinations and choose the best one based on cross-validation. GridSearchCV will try combinations within the previously defined space. For example, for a random forest classifier, you might want to test the maximum depth of several different trees. GridSearchCV provides all possible values for each hyperparameter and looks at all combinations. Optuna uses its own history of attempts within the defined search space to determine which values to try next.
- Python Tutorial . flask 1540 2023-04-12 19:46:15
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- Eight Python libraries that can boost your data science productivity and save valuable time
- When doing data science, you can waste a lot of time coding and waiting for your computer to run something. So I have chosen some Python libraries that can help you save your precious time. 1. OptunaOptuna is an open source hyperparameter optimization framework that can automatically find the best hyperparameters for machine learning models. The most basic (and probably well-known) alternative is sklearn's GridSearchCV, which will try multiple hyperparameter combinations and choose the best one based on cross-validation. GridSearchCV will try combinations within the previously defined space. For example, for a random forest classifier, you might want to test the maximum depth of several different trees. GridSea
- Python Tutorial . flask 1225 2023-04-12 17:01:19